Applied Scientist, Supply Chain Optimization Job ID: Amazon UK Services Ltd. Amazon Supply Chain forms the backbone of the fastest growing e-commerce business in the world. The sheer growth of the business and the company's mission "to be Earth's most customer-centric company" makes the customer fulfillment business bigger and more complex with each passing year. The SC Optimization and Automation team within SCOT organization - Supply Chain Optimization Technology - is looking for an exceptionally talented Scientist to tackle complex and ambiguous optimization and forecasting problems for our WW fulfillment network. The team owns the optimization of our Supply Chain from our suppliers to our customers. We are also responsible for analyzing the performance of our Supply Chain end-to-end and deploying Operations Research, Machine Learning, Statistics and Econometrics models to improve decision making within our organization, including forecasting, planning and executing our network. We work closely with other Supply Chain Optimization Technology teams, with whom we own the systems and the inputs to plan our networks, the worldwide scientific community, and with our internal WW stakeholders within Supply Chain, Transportation, Store and Finance. We are looking for an experienced candidate having a well-rounded technical/scientific background, and deep expertise in large-scale non-convex non-linear OR optimization (inc. stochastic), as well as forecasting (inc. probabilistic). The candidates should have an history of delivering complex scientific projects end-to-end, and is comfortable in developing long term scientific solutions while ensuring the continuous delivery of incremental model improvements and results in an ever-changing operational environment. As an Applied Scientist, you will design, develop and deploy robust and scalable scientific solutions via Operations Research and Machine Learning algorithms, especially in the context of stochastic customer demand and other sources of uncertainty requiring to move past deterministic and linear optimization. You will partner with other tech and science teams, operations, finance to identify opportunities to improve our processes in order to drive efficiency improvements in our Fulfillment Center network flows. This role requires a self-starter aptitude for independent initiative and the ability to influence partner scientific and operational teams so to drive innovation in supply chain planning and execution. You are passionate, results-oriented, and inventive scientist who obsesses over the quality of your solutions and their fast and scalable implementation to address and anticipate customer needs. Key job responsibilities - Build state-of-the art, robust, and scalable optimization and forecasting algorithms to drive optimal inventory placement and product flows in non-convex, non-linear, and stochastic optimization settings - Design and engineer algorithms using Cloud-based state-of-the art software development techniques - Think multiple steps ahead and develop for long term solutions while continuously delivering incremental improvements to existing ones - Prototype fast, ensure early adoption via pilots, integrate feedback into the models, and iterate - Operationalize (i.e. deliver) your science solutions by closely partnering with internal customers, understand their needs/blockers and influence their roadmap - Lead complex analysis and clearly communicate results and recommendations to leadership - Act as an active member of the science community by researching, applying and publishing internally/externally the latest OR/ML techniques from both academia and industry BASIC QUALIFICATIONS - PhD, or a Master's degree and experience applying theoretical models in an applied environment - Experience in solving business problems through machine learning, data mining and statistical algorithms - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - 3+ years experience in commercial OR tools (e.g. CPLEX, Gurobi, XPRESS) - 3+ years experience in developing OR algorithm for non-convex and non-linear optimization problems - 2+ years experience with Stochastic Optimization algorithms (e.g. Stochastic Linear Programming, Stochastic Dynamic Programming) and ML for Probabilistic Forecasting - Sharp analytical abilities, excellent written and verbal communication skills - Ability to handle ambiguity and fast-paced environment PREFERRED QUALIFICATIONS - Experience in professional software development - Reinforcement Learning - Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance - Experience diving into data to discover hidden patterns and of conducting error/deviation analysis - Familiarity with Operations concepts - Planning, Forecasting, Optimization, and Customer experience - gained through work experience or graduate level education - Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2 Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability or other legally protected status.
Aug 05, 2025
Full time
Applied Scientist, Supply Chain Optimization Job ID: Amazon UK Services Ltd. Amazon Supply Chain forms the backbone of the fastest growing e-commerce business in the world. The sheer growth of the business and the company's mission "to be Earth's most customer-centric company" makes the customer fulfillment business bigger and more complex with each passing year. The SC Optimization and Automation team within SCOT organization - Supply Chain Optimization Technology - is looking for an exceptionally talented Scientist to tackle complex and ambiguous optimization and forecasting problems for our WW fulfillment network. The team owns the optimization of our Supply Chain from our suppliers to our customers. We are also responsible for analyzing the performance of our Supply Chain end-to-end and deploying Operations Research, Machine Learning, Statistics and Econometrics models to improve decision making within our organization, including forecasting, planning and executing our network. We work closely with other Supply Chain Optimization Technology teams, with whom we own the systems and the inputs to plan our networks, the worldwide scientific community, and with our internal WW stakeholders within Supply Chain, Transportation, Store and Finance. We are looking for an experienced candidate having a well-rounded technical/scientific background, and deep expertise in large-scale non-convex non-linear OR optimization (inc. stochastic), as well as forecasting (inc. probabilistic). The candidates should have an history of delivering complex scientific projects end-to-end, and is comfortable in developing long term scientific solutions while ensuring the continuous delivery of incremental model improvements and results in an ever-changing operational environment. As an Applied Scientist, you will design, develop and deploy robust and scalable scientific solutions via Operations Research and Machine Learning algorithms, especially in the context of stochastic customer demand and other sources of uncertainty requiring to move past deterministic and linear optimization. You will partner with other tech and science teams, operations, finance to identify opportunities to improve our processes in order to drive efficiency improvements in our Fulfillment Center network flows. This role requires a self-starter aptitude for independent initiative and the ability to influence partner scientific and operational teams so to drive innovation in supply chain planning and execution. You are passionate, results-oriented, and inventive scientist who obsesses over the quality of your solutions and their fast and scalable implementation to address and anticipate customer needs. Key job responsibilities - Build state-of-the art, robust, and scalable optimization and forecasting algorithms to drive optimal inventory placement and product flows in non-convex, non-linear, and stochastic optimization settings - Design and engineer algorithms using Cloud-based state-of-the art software development techniques - Think multiple steps ahead and develop for long term solutions while continuously delivering incremental improvements to existing ones - Prototype fast, ensure early adoption via pilots, integrate feedback into the models, and iterate - Operationalize (i.e. deliver) your science solutions by closely partnering with internal customers, understand their needs/blockers and influence their roadmap - Lead complex analysis and clearly communicate results and recommendations to leadership - Act as an active member of the science community by researching, applying and publishing internally/externally the latest OR/ML techniques from both academia and industry BASIC QUALIFICATIONS - PhD, or a Master's degree and experience applying theoretical models in an applied environment - Experience in solving business problems through machine learning, data mining and statistical algorithms - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - 3+ years experience in commercial OR tools (e.g. CPLEX, Gurobi, XPRESS) - 3+ years experience in developing OR algorithm for non-convex and non-linear optimization problems - 2+ years experience with Stochastic Optimization algorithms (e.g. Stochastic Linear Programming, Stochastic Dynamic Programming) and ML for Probabilistic Forecasting - Sharp analytical abilities, excellent written and verbal communication skills - Ability to handle ambiguity and fast-paced environment PREFERRED QUALIFICATIONS - Experience in professional software development - Reinforcement Learning - Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance - Experience diving into data to discover hidden patterns and of conducting error/deviation analysis - Familiarity with Operations concepts - Planning, Forecasting, Optimization, and Customer experience - gained through work experience or graduate level education - Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2 Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability or other legally protected status.
C3.ai, Inc. (NYSE:AI) is a leading Enterprise AI software provider for accelerating digital transformation. The proven C3 AI Platform provides comprehensive services to build enterprise-scale AI applications more efficiently and cost-effectively than alternative approaches. The C3 AI Platform supports the value chain in any industry with prebuilt, configurable, high-value AI applications for reliability, fraud detection, sensor network health, supply network optimization, energy management, anti-money laundering, and customer engagement. Learn more at: C3 AI As a member of the C3 AI Data Science team, you will work with some of the largest companies on the planet helping them build the next generation of AI-powered enterprise applications on the C3 AI Platform. You will work directly with researchers, data scientists, software engineers, and subject matter experts in the definition of new generative AI capabilities able to provide our customers with the information they need to make proper decisions and enable their digital transformation. Qualified candidates will have an in-depth knowledge of the most common Large Language Models (LLMs) and Retrieval Methods, know how to train and fine-tune LLMs, and design and implement LLM-powered agents and tools at scale. Responsibilities: Design and deploy Generative AI solutions, such as information retrieval and coding assistance, for industrial customers. Collaborate with Generative AI subject matter experts from C3 AI, its customer teams, and academia to identify, design, and implement innovative and differentiated solutions using cutting-edge research on LLMs and Generative AI. Drive the adoption and scalability of Generative AI offerings within C3 AI products. Qualifications: MS or PhD in Computer Science, Electrical Engineering, Statistics, Robotics or equivalent fields. Applied Machine Learning experience (regression and classification, supervised, and unsupervised learning). Strong mathematical background (linear algebra, calculus, probability, and statistics). Proficiency in Python and object-oriented programming. Strong experience working with machine learning and natural language processing techniques and tools. Strong experience using Generative AI models, with a good understanding of deep learning model classes such as GPT, VAE, and GANs, as well as their hyperparameters. Strong experience with retrieval methods e.g. using embeddings. Strong experience using key Python packages for data wrangling, machine learning and deep learning such as pandas, sklearn, TensorFlow, torch, transformers, LangChain, etc. Experience in Prompt Engineering and few-shot techniques to enhance LLM's performance on specific tasks. Experience with training and fine-tuning deep learning models, especially LLMs, and how to tune hyperparameters to ensure task generalization. Ability to drive a project and work both independently and within a cross-functional team. Smart, motivated, can-do attitude, innovative and seeks to make a difference in a fast-paced environment. Excellent verbal and written communication, able to articulate complex concepts with a non-technical audience. Preferred Qualifications: Experience with embedding model training and retrieval method evaluation approaches. Experience with LLM architectures, adapters, Mixture of Experts (MoEs) pretraining and fine-tuning techniques. Experience with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches. Experience with reinforcement learning approaches in the context of fine-tuning LLM outputs. Experience with time series analysis and multivariate time series modeling. C3 AI provides excellent benefits and a competitive compensation package. C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.
Feb 18, 2025
Full time
C3.ai, Inc. (NYSE:AI) is a leading Enterprise AI software provider for accelerating digital transformation. The proven C3 AI Platform provides comprehensive services to build enterprise-scale AI applications more efficiently and cost-effectively than alternative approaches. The C3 AI Platform supports the value chain in any industry with prebuilt, configurable, high-value AI applications for reliability, fraud detection, sensor network health, supply network optimization, energy management, anti-money laundering, and customer engagement. Learn more at: C3 AI As a member of the C3 AI Data Science team, you will work with some of the largest companies on the planet helping them build the next generation of AI-powered enterprise applications on the C3 AI Platform. You will work directly with researchers, data scientists, software engineers, and subject matter experts in the definition of new generative AI capabilities able to provide our customers with the information they need to make proper decisions and enable their digital transformation. Qualified candidates will have an in-depth knowledge of the most common Large Language Models (LLMs) and Retrieval Methods, know how to train and fine-tune LLMs, and design and implement LLM-powered agents and tools at scale. Responsibilities: Design and deploy Generative AI solutions, such as information retrieval and coding assistance, for industrial customers. Collaborate with Generative AI subject matter experts from C3 AI, its customer teams, and academia to identify, design, and implement innovative and differentiated solutions using cutting-edge research on LLMs and Generative AI. Drive the adoption and scalability of Generative AI offerings within C3 AI products. Qualifications: MS or PhD in Computer Science, Electrical Engineering, Statistics, Robotics or equivalent fields. Applied Machine Learning experience (regression and classification, supervised, and unsupervised learning). Strong mathematical background (linear algebra, calculus, probability, and statistics). Proficiency in Python and object-oriented programming. Strong experience working with machine learning and natural language processing techniques and tools. Strong experience using Generative AI models, with a good understanding of deep learning model classes such as GPT, VAE, and GANs, as well as their hyperparameters. Strong experience with retrieval methods e.g. using embeddings. Strong experience using key Python packages for data wrangling, machine learning and deep learning such as pandas, sklearn, TensorFlow, torch, transformers, LangChain, etc. Experience in Prompt Engineering and few-shot techniques to enhance LLM's performance on specific tasks. Experience with training and fine-tuning deep learning models, especially LLMs, and how to tune hyperparameters to ensure task generalization. Ability to drive a project and work both independently and within a cross-functional team. Smart, motivated, can-do attitude, innovative and seeks to make a difference in a fast-paced environment. Excellent verbal and written communication, able to articulate complex concepts with a non-technical audience. Preferred Qualifications: Experience with embedding model training and retrieval method evaluation approaches. Experience with LLM architectures, adapters, Mixture of Experts (MoEs) pretraining and fine-tuning techniques. Experience with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches. Experience with reinforcement learning approaches in the context of fine-tuning LLM outputs. Experience with time series analysis and multivariate time series modeling. C3 AI provides excellent benefits and a competitive compensation package. C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.
Get started with your online application. The Data & Science Org At Deliveroo, we have a world-class data and science organisation with a mission to enable the highest quality human and machine decision-making. We work throughout the company - in product, business and platform teams to answer some of the most interesting questions out there. For example, how can we connect restaurants, riders and customers most efficiently in order to deliver food as quickly as possible? How do data and technology help restaurants to grow as consumer habits change? How can we predict what someone wants to order for dinner long before the idea has even crossed their mind? These are just some of the tough problems we are solving at Deliveroo. There is no challenge that cannot be yours; the scope for growth and personal impact is enormous. Data Scientists and Machine Learning Engineers at Deliveroo belong to an expert, thoughtful, and active community with guest lecturers, a robust technical review process, a career progression framework, and plenty of opportunities to learn new things. The Role As an Operational Research Scientist, you will play a crucial role in developing, implementing, and maintaining cutting-edge products that leverage optimization techniques. Your responsibilities will involve engineering sophisticated operational research algorithms, as well as refining and updating existing systems. In this team, you will develop the algorithmic and machine-learning systems that power Deliveroo's delivery network. You will work in a cross-functional team alongside engineers, data scientists and product managers to develop systems that make automated decisions at massive scale. The team has independence and works on some of the most interesting problems at the intersection of riders, consumers, and restaurants. We evaluate the performance of all our decision-making machines through our world-class experimentation platform. You will report into a ML/OR Manager. This is a hybrid role that will be based in London. You will: Optimise our delivery network by making rider assignment decisions; predicting how long a leg of the delivery journey will take; or mitigating real-time delays. Enhance our simulation capabilities to more accurately predict the effects of algorithmic changes on our delivery network. Optimise consumer and rider fees. Also, you will work alongside people who work on: The consumer experience by showing the most relevant restaurants and dishes. Detecting fraud and abuse from consumers, riders, and restaurants. Assisting restaurants in optimising their presence on Deliveroo, for example by recommending that they improve their menus or photography, or add a popular dish. Creating an ML platform to improve our ML and optimisation capabilities. Requirements: You are someone who knows the fundamentals of operational research and when they should be applied through a relevant PhD or work experience. Proven experience in developing and applying optimization models, algorithms, and metaheuristic techniques in a logistics or supply chain context. You can translate fuzzy logistics and delivery problems or objectives into a well-thought-out algorithmic solution. You get satisfaction from seeing your algorithms shipped and driving measurable impact to the business. Strong programming skills in one of the languages such as Python, Rust, C, C++, or Java, with a focus on algorithm design rather than software engineering. Experience in combinatorial optimisation problems. A bias to simplicity, where you care most about achieving impact. Nice to haves: Experience in solving Vehicle Routing Problems (VRP) and/or building large scale delivery network simulations. Experience in discrete event simulations. Experience in any of the following areas: algorithms and data structures, parallel and distributed computing, high-performance computing. Why Deliveroo Our mission is to transform the way you shop and eat, bringing the neighbourhood to your door by connecting consumers, restaurants, shops and riders. We are transforming the way the world eats and shops by making access to food and products more convenient and enjoyable. We are a technology-driven company at the forefront of the most rapidly expanding industry in the world. We are still a small team, making a very large impact, looking to answer some of the most interesting questions out there. We move fast, value autonomy and ownership, and we are always looking for new ideas. At Deliveroo we know that people are the heart of the business and we prioritise their welfare. Benefits differ by country, but we offer many benefits in areas including healthcare, well-being, parental leave, pensions, and generous annual leave allowances, including time off to support a charitable cause of your choice. Benefits are country-specific, please ask your recruiter for more information. Diversity At Deliveroo, we believe a great workplace is one that represents the world we live in and how beautifully diverse it can be. That means we have no judgement when it comes to any one of the things that make you who you are - your gender, race, sexuality, religion or a secret aversion to coriander. All you need is a passion for (most) food and a desire to be part of one of the fastest-growing businesses in a rapidly growing industry. We are committed to diversity, equity and inclusion in all aspects of our hiring process. We recognise that some candidates may require adjustments to apply for a position or fairly participate in the interview process. If you require any adjustments, please don't hesitate to let us know. We will make every effort to provide the necessary adjustments to ensure you have an equitable opportunity to succeed.
Feb 13, 2025
Full time
Get started with your online application. The Data & Science Org At Deliveroo, we have a world-class data and science organisation with a mission to enable the highest quality human and machine decision-making. We work throughout the company - in product, business and platform teams to answer some of the most interesting questions out there. For example, how can we connect restaurants, riders and customers most efficiently in order to deliver food as quickly as possible? How do data and technology help restaurants to grow as consumer habits change? How can we predict what someone wants to order for dinner long before the idea has even crossed their mind? These are just some of the tough problems we are solving at Deliveroo. There is no challenge that cannot be yours; the scope for growth and personal impact is enormous. Data Scientists and Machine Learning Engineers at Deliveroo belong to an expert, thoughtful, and active community with guest lecturers, a robust technical review process, a career progression framework, and plenty of opportunities to learn new things. The Role As an Operational Research Scientist, you will play a crucial role in developing, implementing, and maintaining cutting-edge products that leverage optimization techniques. Your responsibilities will involve engineering sophisticated operational research algorithms, as well as refining and updating existing systems. In this team, you will develop the algorithmic and machine-learning systems that power Deliveroo's delivery network. You will work in a cross-functional team alongside engineers, data scientists and product managers to develop systems that make automated decisions at massive scale. The team has independence and works on some of the most interesting problems at the intersection of riders, consumers, and restaurants. We evaluate the performance of all our decision-making machines through our world-class experimentation platform. You will report into a ML/OR Manager. This is a hybrid role that will be based in London. You will: Optimise our delivery network by making rider assignment decisions; predicting how long a leg of the delivery journey will take; or mitigating real-time delays. Enhance our simulation capabilities to more accurately predict the effects of algorithmic changes on our delivery network. Optimise consumer and rider fees. Also, you will work alongside people who work on: The consumer experience by showing the most relevant restaurants and dishes. Detecting fraud and abuse from consumers, riders, and restaurants. Assisting restaurants in optimising their presence on Deliveroo, for example by recommending that they improve their menus or photography, or add a popular dish. Creating an ML platform to improve our ML and optimisation capabilities. Requirements: You are someone who knows the fundamentals of operational research and when they should be applied through a relevant PhD or work experience. Proven experience in developing and applying optimization models, algorithms, and metaheuristic techniques in a logistics or supply chain context. You can translate fuzzy logistics and delivery problems or objectives into a well-thought-out algorithmic solution. You get satisfaction from seeing your algorithms shipped and driving measurable impact to the business. Strong programming skills in one of the languages such as Python, Rust, C, C++, or Java, with a focus on algorithm design rather than software engineering. Experience in combinatorial optimisation problems. A bias to simplicity, where you care most about achieving impact. Nice to haves: Experience in solving Vehicle Routing Problems (VRP) and/or building large scale delivery network simulations. Experience in discrete event simulations. Experience in any of the following areas: algorithms and data structures, parallel and distributed computing, high-performance computing. Why Deliveroo Our mission is to transform the way you shop and eat, bringing the neighbourhood to your door by connecting consumers, restaurants, shops and riders. We are transforming the way the world eats and shops by making access to food and products more convenient and enjoyable. We are a technology-driven company at the forefront of the most rapidly expanding industry in the world. We are still a small team, making a very large impact, looking to answer some of the most interesting questions out there. We move fast, value autonomy and ownership, and we are always looking for new ideas. At Deliveroo we know that people are the heart of the business and we prioritise their welfare. Benefits differ by country, but we offer many benefits in areas including healthcare, well-being, parental leave, pensions, and generous annual leave allowances, including time off to support a charitable cause of your choice. Benefits are country-specific, please ask your recruiter for more information. Diversity At Deliveroo, we believe a great workplace is one that represents the world we live in and how beautifully diverse it can be. That means we have no judgement when it comes to any one of the things that make you who you are - your gender, race, sexuality, religion or a secret aversion to coriander. All you need is a passion for (most) food and a desire to be part of one of the fastest-growing businesses in a rapidly growing industry. We are committed to diversity, equity and inclusion in all aspects of our hiring process. We recognise that some candidates may require adjustments to apply for a position or fairly participate in the interview process. If you require any adjustments, please don't hesitate to let us know. We will make every effort to provide the necessary adjustments to ensure you have an equitable opportunity to succeed.
Applied Scientist, SCOT IPC SimJob ID: Amazon UK Services Ltd.Job summary This job opportunity requires relocation to UK - opening is available in London or Cambridge. Are you looking for a challenge? Imagine being part of a team that owns one of the largest supply chain simulation systems in the world to predict inventory flows for the millions of items available on ( ) worldwide. Inventory planning involves many algorithms to buy inventory in the right quantities, at the right frequencies, from the right vendors, and assigning to the best warehouse to fulfill customer demand to optimize long term free cash flow for Amazon. Our system lives at the heart of these algorithms, keeping up with the rapid pace of optimization improvements and simulating how they interact with each other. We simulate what these systems will do for months into the future, predicting inventory flows and key operational and financial metrics across the network. This experimentation platform is critical in understanding labor needs, managing our network capacity, and allowing continued optimizations to the many algorithms we simulate. Imagine enabling Amazon's supply chain systems to make data driven decisions based on simulations of trillions of inventory events per day. Every time an Amazon customer makes a purchase, a number of systems are involved: these systems help optimize inventory acquisition, enable a number of purchase options, ensure great pricing, store products so they are available for fast delivery, and minimize package frustration. The Supply Chain Optimization Technology (SCOT - ) group develops and manages these systems. We are central to Amazon customers' ability to find what they want and get it when they want it. Within SCOT, the IPC Sim (Inventory Planning and Control Simulation) team is responsible for designing and executing the simulations and experiments that measure the impact of SCOT initiatives, as well as predicting inventory flows for labor planning. Amazon's Cambridge UK based Simulation team is looking for an experienced and passionate Applied Scientist (AS) to join our fast-paced stimulating environment, to help invent the future of retail with technology. The Inventory Panning and Control (IPC) Simulation team is part of the Supply Chain Optimization Technologies (SCOT) organization. The charter of the SCOT team is to maximize Amazon's return on our inventory investment in terms of Free Cash Flow, and customer satisfaction. We accomplish this by applying simulation, advanced statistical methods, and empirical analysis to predict and evaluate Amazon's inventory needs. The IPC Sim team builds systems that allow SCOT to answer "what if?" questions about our supply chain, our fulfilment network, and our customers. This puts the IPC Sim team at the nexus of operations, logistics, capacity planning, and our retail business teams. To learn more about Supply Chain Optimization Technologies (SCOT) at Amazon, watch this amazing video: To learn more about the work of the team read this blog post: As an Applied Scientist you will design and develop new machine learning methods that will form the backbone of the simulation and experimentation systems that drive Amazon's retail business forward. You will have access to large datasets with billions of orders and products to build large-scale machine learning systems. Areas of work in this domain include probabilistic modelling, emulation using Gaussian processes, Bayesian optimization and probabilistic numerics, statistical analysis of computer experiments, adaptive experimental design and causal inference. You will work with Researchers, Data Scientists, Data Engineers, Software Engineers, and Product Managers across multiple teams. Successful outstanding candidates will bring strong technical and analytical abilities, combined with a passion for delivering results for customers, internal and external. This role requires a high degree of ownership, and a drive, to solve some of the most challenging data and engineering problems in retail. Amazon is an Equal Opportunity - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. BASIC QUALIFICATIONS Undergraduate degree in computer science, software engineering or undergraduate degree in numerical discipline ( physics, maths, engineering). Completed PhD in machine learning or statistics or equivalent experience. Ability to communicate scientific results and ideas in writing, as evidenced by papers in top machine learning conferences (NeurIPS, ICML, AISTATS, etc) and/or statistical journals (JASA, Annals of statistics, etc) Strong verbal and written communication skills and an ability to work in a team environment Proven hands-on experience in predictive modelling and analysis. 4+ years of experience using scripting languages ( Python) PREFERRED QUALIFICATIONS Expertise in Bayesian computation, Gaussian processes, kernel methods, surrogate modelling (emulation), optimisation, experimental design. Experience in python's machine learning and data science stack (tensorflow/pytorch/mxnet, numpy, pandas, matplotlib, scikit-learn, etc). Ability to convey rigorous mathematical concepts and considerations to non-experts. Ability to distill problem definitions, models, and constraints from informal business requirements; and to deal with ambiguity and competing objectives. Strong software development skills. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need an adjustment during the application and hiring process, including support for the interview or onboarding process, please contact the Applicant-Candidate Accommodation Team (ACAT), Monday through Friday from 7:00 am GMT - 4:00 pm GMT. If calling directly from the United Kingdom, please dial (tel: ). If calling from Ireland, please dial (tel: ).
Sep 23, 2022
Full time
Applied Scientist, SCOT IPC SimJob ID: Amazon UK Services Ltd.Job summary This job opportunity requires relocation to UK - opening is available in London or Cambridge. Are you looking for a challenge? Imagine being part of a team that owns one of the largest supply chain simulation systems in the world to predict inventory flows for the millions of items available on ( ) worldwide. Inventory planning involves many algorithms to buy inventory in the right quantities, at the right frequencies, from the right vendors, and assigning to the best warehouse to fulfill customer demand to optimize long term free cash flow for Amazon. Our system lives at the heart of these algorithms, keeping up with the rapid pace of optimization improvements and simulating how they interact with each other. We simulate what these systems will do for months into the future, predicting inventory flows and key operational and financial metrics across the network. This experimentation platform is critical in understanding labor needs, managing our network capacity, and allowing continued optimizations to the many algorithms we simulate. Imagine enabling Amazon's supply chain systems to make data driven decisions based on simulations of trillions of inventory events per day. Every time an Amazon customer makes a purchase, a number of systems are involved: these systems help optimize inventory acquisition, enable a number of purchase options, ensure great pricing, store products so they are available for fast delivery, and minimize package frustration. The Supply Chain Optimization Technology (SCOT - ) group develops and manages these systems. We are central to Amazon customers' ability to find what they want and get it when they want it. Within SCOT, the IPC Sim (Inventory Planning and Control Simulation) team is responsible for designing and executing the simulations and experiments that measure the impact of SCOT initiatives, as well as predicting inventory flows for labor planning. Amazon's Cambridge UK based Simulation team is looking for an experienced and passionate Applied Scientist (AS) to join our fast-paced stimulating environment, to help invent the future of retail with technology. The Inventory Panning and Control (IPC) Simulation team is part of the Supply Chain Optimization Technologies (SCOT) organization. The charter of the SCOT team is to maximize Amazon's return on our inventory investment in terms of Free Cash Flow, and customer satisfaction. We accomplish this by applying simulation, advanced statistical methods, and empirical analysis to predict and evaluate Amazon's inventory needs. The IPC Sim team builds systems that allow SCOT to answer "what if?" questions about our supply chain, our fulfilment network, and our customers. This puts the IPC Sim team at the nexus of operations, logistics, capacity planning, and our retail business teams. To learn more about Supply Chain Optimization Technologies (SCOT) at Amazon, watch this amazing video: To learn more about the work of the team read this blog post: As an Applied Scientist you will design and develop new machine learning methods that will form the backbone of the simulation and experimentation systems that drive Amazon's retail business forward. You will have access to large datasets with billions of orders and products to build large-scale machine learning systems. Areas of work in this domain include probabilistic modelling, emulation using Gaussian processes, Bayesian optimization and probabilistic numerics, statistical analysis of computer experiments, adaptive experimental design and causal inference. You will work with Researchers, Data Scientists, Data Engineers, Software Engineers, and Product Managers across multiple teams. Successful outstanding candidates will bring strong technical and analytical abilities, combined with a passion for delivering results for customers, internal and external. This role requires a high degree of ownership, and a drive, to solve some of the most challenging data and engineering problems in retail. Amazon is an Equal Opportunity - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. BASIC QUALIFICATIONS Undergraduate degree in computer science, software engineering or undergraduate degree in numerical discipline ( physics, maths, engineering). Completed PhD in machine learning or statistics or equivalent experience. Ability to communicate scientific results and ideas in writing, as evidenced by papers in top machine learning conferences (NeurIPS, ICML, AISTATS, etc) and/or statistical journals (JASA, Annals of statistics, etc) Strong verbal and written communication skills and an ability to work in a team environment Proven hands-on experience in predictive modelling and analysis. 4+ years of experience using scripting languages ( Python) PREFERRED QUALIFICATIONS Expertise in Bayesian computation, Gaussian processes, kernel methods, surrogate modelling (emulation), optimisation, experimental design. Experience in python's machine learning and data science stack (tensorflow/pytorch/mxnet, numpy, pandas, matplotlib, scikit-learn, etc). Ability to convey rigorous mathematical concepts and considerations to non-experts. Ability to distill problem definitions, models, and constraints from informal business requirements; and to deal with ambiguity and competing objectives. Strong software development skills. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need an adjustment during the application and hiring process, including support for the interview or onboarding process, please contact the Applicant-Candidate Accommodation Team (ACAT), Monday through Friday from 7:00 am GMT - 4:00 pm GMT. If calling directly from the United Kingdom, please dial (tel: ). If calling from Ireland, please dial (tel: ).
