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Analyst, Quantitative Analyst - Risk Analytics Group page is loaded Analyst, Quantitative Analyst - Risk Analytics Group Apply locations London time type Full time posted on Posted 2 Days Ago job requisition id -WD Do you want your voice heard and your actions to count? Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world's leading financial groups. Across the globe, we're 120,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world. With a vision to be the world's most trusted financial group, it's part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career. Join MUFG, where being inspired is expected and making a meaningful impact is rewarded. OVERVIEW OF THE DEPARTMENT/SECTION The Risk Analytics Group (RAG) is a specialised area within the Risk Department, responsible for Market Risk Models, Capital Models, Counterparty Exposure Models and Pricing Model Validation. The team members have strong quantitative skills and the team head reports to the local and international Chief Risk Officer. MAIN PURPOSE OF THE ROLE The main responsibilities of the Counterparty Exposure Analytics and Standardised Models sub-team of RAG main are the development and maintenance of the models for Potential Future Exposure (PFE), Standardised Initial Margin Model (SIMM) and FRTB-ASA (Fundamental Review of the Trading Book, Advanced Standardised Approach). The team also covers stress testing models and Standardised Approach for Credit Valuation Adjustment (SA-CVA). ISDA SIMM is used for Initial Margin. PFE models are used to measure Counterparty Exposure, internal control limits and partly in economic capital calculations. The PFE simulation covers Rates, FX, Credit, inflation, Equity and Bond Spreads, across derivatives, Repo and Securities Borrowing and Lending transactions. The successful candidate will be responsible for Initial Margin calculations and ongoing performance tests. The model is an internally developed implementation of the ISDA model, which is sensitivity-based. The role will also include other tasks within the sub-team, such as pre-trade PFE analytics to support the Front Office recalibrating model parameters, stress PFE metrics and PFE model performance monitoring. The role will report to Head of Counterparty Exposure Analytics and Standardised Models. The candidate will work closely with other team members in RAG, Credit Risk Management, the IT development teams, risk model validators, Legal, Operations, Data and Front Office teams. The successful candidate will work in an inclusive and proactive way, ensuring that the team takes the lead in new model development and resolves issues as they arise, communicating clearly in management reports. KEY RESPONSIBILITIES In this role, you will be responsible for counterparty risk modelling across MUFG's banking arm and securities business under a dual-hat arrangement. Under this arrangement, you will act and make decisions on behalf of both the bank and the securities business, subject to the same remit and level of authority, and irrespective of the entity which employs you. You will: Maintain specifications of the SIMM risk model calculation and its inputs Specify and test system changes to implement improvements Develop, maintain and improve counterparty exposure models Assist with PFE model development and maintenance, including calibration and back-testing Reviewing stress exposure metrics Test risk output for new products to be handled in the models Run model performance tests for both model assumptions and implementation, and improve this process Analyse results of ongoing model performance tests, investigate issues and escalate results where appropriate Prepare summary reporting to model oversight committee, MUFG Group and to regulators Improve existing operational controls around the models and propose new ones to increase robustness Development of the SIMM analytics library Python package Support business and credit department requests in investigations into pre-trade calculations Support Legal and Operations department in managing counterparty relationships Ad-hoc projects as required, including collaboration with Market Risk Analytics and model validation. Proactively contribute to wider Risk function initiatives and projects. WORK EXPERIENCE Essential: Previous experience in pricing models Approx. 2 years total relevant experience Preferred: Previous experience in a risk-related role Experience in SIMM, FRTB-ASA or exposure models Experience in banking, consulting, auditor or other relevant financial services SKILLS AND EXPERIENCE Required Finance or highly numerate education (Maths, Statistics, Engineering, Computer Science, Finance) Understanding of financial markets and products including derivatives Familiarity with principles of derivatives pricing Experience with Python/R/Excel/VBA Desirable Understanding of counterparty exposure measures such as PFE, EE, CVA Knowledge of advanced programming languages (C#, C++) Knowledge of stochastic calculus PERSONAL REQUIREMENTS Excellent communication skills with the ability to adjust to different audiences Highly motivated and innovative, able to work on own initiative Excellent accuracy and attention to detail with an analytical mind-set Good team player with professional attitude Good time management and ability to prioritise Ability to manage large workloads and tight deadlines, balancing urgent tasks and longer term projects Strong decision making skills, the ability to demonstrate sound judgement Strong problem solving skills Strong numerical skills We are open to considering flexible working requests in line with organisational requirements. MUFG is committed to embracing diversity and building an inclusive culture where all employees are valued, respected and their opinions count. We support the principles of equality, diversity and inclusion in recruitment and employment, and oppose all forms of discrimination on the grounds of age, sex, gender, sexual orientation, disability, pregnancy and maternity, race, gender reassignment, religion or belief and marriage or civil partnership. We make our recruitment decisions in a non-discriminatory manner in accordance with our commitment to identifying the right skills for the right role and our obligations under the law. 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The basics Your title will be Staff Product Engineer This role pays £170-£200k. We'll match your salary with the same amount in share options, vesting over 4 years. Matt, Cofounder and CTO, is the hiring manager We work Mon-Thu in our office in Chancery Lane, London, Fri from anywhere What are we building? Walk around the average office and you'll see people's days taken up by emails, Slack and meetings instead of real work. People in client facing roles - think estate agents, insurance brokers, recruiters - feel this pain most acutely. Instead of meeting clients, they spend hours doing admin. Following up. Scheduling meetings, then taking notes on them. Answering questions they've been asked a thousand times. Sorting through the mess that is their inbox. We've built an AI executive assistant that looks at all your emails, messages and meetings, and uses that knowledge to answer your email, schedule meetings, take next steps from meetings and organise your inbox. How has it been going? Since launching in April 2024, we've gone from $0 to $13m in ARR and raised a $30m Series B from top investors. What do we value? Autonomy, agency, and ownership. Each of our Product Engineers owns one of Fyxer AI's products. They own both the product strategy (we have no product managers and have no plans for that to change) and the execution of that strategy. They choose when to bring in qualitative data (customer interviews, surveys etc) and quantitative, supported by our data engineering department. We're very intentional about adding new people. We think a small team of exceptional people working hard at a problem they care about will always beat a larger, less focused team. That does mean you'll need to bring an intensity to this role that might not be asked at other companies. But it also means you will be fast tracked into more senior roles and responsibilities far earlier. What will I do? In short, own one of Fyxer AI's most important products: Decide on metrics for your product, and gain an intuitive understanding of its value by using it yourself and speaking to customers. Use quantitative data, customer insight, and product sense to build a strategy for your product area, and prioritise initiatives within that strategy Execute your strategy by coding up your ideas Manage and improve reliability in your product area, by monitoring logs, analysing support tickets and fixing bugs A key area for responsibility will be mentoring and developing other product engineers, setting the product direction for a large area of the business, and setting the direction for the tooling the team uses internally to be productive. What does our ideal hire look like? You've worked at an early stage tech company as a staff or lead engineer ( You have an expert level understanding of Typescript and serverless architecture. If you don't have these, you shouldn't apply. You want to get involved in product work, rather than just being handed tickets. You'll be expected to come up with features autonomously, by reading customer feedback and analysing usage data You can function as a fullstack engineer, working on client and server side code, and answering data questions using SQL High interest in AI and the problem we're using it to solve Urgency and intensity in your work Our tech stack Broadly, we use a fairly typical serverless Typescript stack. It's not a requirement to have worked with every tool in this stack, but the more the better! Typescript for all production code Firestore as our production database Firebase Auth as our auth system Backend deployed on Firebase Functions, and making use of PubSub and Cloud Storage React frontend, using ShadCN for components, TailwindCSS for styling, React Query for state management Posthog for frontend analytics (events, sessions, feature flags, experiments) BigQuery as our data warehouse, with Metabase for data visualization. Production data and Posthog events both stream into it so data is in one place. Sentry and Google Cloud Logging for monitoring Github Actions for CI/CD The application process Submit your CV (no need for a cover letter) An initial call with someone from the Fyxer AI team to review your experience and motivation for joining (30 mins) Product case study, remote (45 minutes) Live coding, remote (60 minutes) Meet team in office (60 minutes)