Staff Data Scientist

At Optimizely, we're on a mission to help people unlock their digital potential. We do that by reinventing how marketing and product teams work to create and optimize digital experiences across all channels. With Optimizely One, our industry-first operating system for marketers, we offer teams flexibility and choice to build their stack their way with our fully SaaS, fully decoupled, and highly composable solution.

We are proud to help more than 10,000 businesses, including H&M, PayPal, Zoom, and Toyota, enrich their customer lifetime value, increase revenue and grow their brands. Our innovation and excellence have earned us numerous recognitions as a leader by industry analysts such as Gartner, Forrester, and IDC, reinforcing our role as a trailblazer in MarTech.

At our core, we believe work is about more than just numbers it's about the people. Our culture is dynamic and constantly evolving, shaped by every employee, their actions and their stories. With over 1500 Optimizers spread across 12 global locations, our diverse team embodies the "One Optimizely" spirit, emphasizing collaboration and continuous improvement, while fostering a culture where every voice is heard and valued.

Join us and become part of a company that's empowering people to unlock their digital potential!

To get a sneak peek into our culture, find us on

Why is this team critical to Optimizely?

Business Impact: Powering Optimizely One, our ML innovations are crucial for defining Optimizely's technological leadership in digital experience platform

High Visibility: ML capabilities developed by this team are central to Optimizely's strategic product roadmap and cross-product integration

Shape the Future: we are positioned to define the next generation of intelligent digital interaction across global brands

We are seeking an exceptional Staff Data Scientist who will architect and technically lead projects dedicated to pushing the boundaries of AI-driven digital experiences. In this pivotal role, you will guide the development of cutting-edge machine learning solutions that not only anticipate but actively shape how global brands engage, understand, and delight their customers through intelligent, predictive, and personalized digital interactions.Some Technologies We Work With:Python primarily, with bits and pieces of typescript and scalaGCP, AWS, Azure - in this order of relevanceGitHub, Docker, GitHub Actions, Terraform, KubernetesPandas, PySpark and SparkVertex AI, Azure OpenAI for LLMs

• Lead the execution of projects in a high-performing data science team, fostering professional growth and creating an inclusive and collaborative environment
• Architect and design scalable machine learning systems that solve complex challenges
• Develop and execute the data science team's strategic roadmap, managing complex projects from conception to deployment
• Make high-impact technical decisions and provide guidance
• Establish best practices in software engineering and machine learning development
• Implement rigorous code quality and testing standards across data science projects
• Support talent acquisition and continuous learning initiatives

• Knowledge of ML model development and deployment frameworks (MLFlow, Kubeflow
• Advanced data querying (SQL) and data engineering pipelines (Airflow
• Extensive experience with comprehensive unit testing, integration testing, and test coverage strategies
• Experience working with Product Management teams and ability to translate complex technical concepts for non-technical stakeholders

PhD's, Master's, or Bachelor's degree in Computer Science, Machine Learning, or related field

Driving Continuous Improvement

Driving for Results

Driving Projects to Completion

Interacting with People at Different Levels

Communicating Effectively

Prioritizing and Organizing Work

Developing Talent

Displaying Technical Expertise

Accepting Responsibility

Optimizely is committed to a diverse and inclusive workplace. Optimizely is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.