Controllers-London-Vice President-Quantitative Engineering

Goldman Sachs
London
2 months ago
Applications closed

Related Jobs

View all jobs

Graduate Electronics Engineer

Senior Data Analyst

Data Analyst

Cloud Data Engineer

Credit Risk Manager

Quantitative Developer

What We Do
At Goldman Sachs, our Engineers don't just make things - we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets.
The Controllers division is responsible for financial control and regulatory obligations of the firm. They safeguard the assets of the firm through an independent scrutiny of the financial information and ensure accurate reporting to internal and external consumers. They provide critical metrics and related analysis to the firm's and divisions' leadership to navigate the evolving business strategy, including incumbent and strategic initiatives. Controllers play an important role in the changing landscape of the firm, including its new business ventures and acquisitions, and ensure that these new initiatives are in line with the regulatory expectations as well as controlled in terms of their incorporation into the firm
Finance engineers help ensure the firm meets all of its financial control and reporting obligations. Working in small and nimble teams, we build critical and complex software to calculate profit and loss (P&L), independently verify valuations, measure and optimize the firm's capital, balance sheet and liquidity metrics, and regulatory filings across the globe.
OUR Impact:
Controllers Strats is responsible for designing and implementing solutions to manage the firm's P&L, independently verify valuations, measure and optimize the firm's capital, balance sheet and liquidity metrics, and regulatory obligations. Our global agile teams (based across Americas, EMEA and Asia) develop and manage the platforms, calculation engines, and analytical tools that controllers, risk management, and deal-making teams use to project, monitor and report externally to regulatory for both regular business activity and under stress scenarios.
YOUR Impact:
We conduct our business in increasingly complex markets. Our people must continually find new ways to provide access to capital, manage risk and provide investment opportunities for our clients to enable them to realize their goals. We judge ourselves on our ability to help clients anticipate and respond to changing market conditions and to create opportunities that merit the trust they place in us.
Controllers Strats is a multidisciplinary group of quantitative experts within the Controllers Division, focusing on independent price verification, regulatory capital measurement, revenue analysis and modelling. The group is primarily responsible for building advanced quantitative models and analytical tools for valuation risk and regulatory capital pertaining to the three areas mentioned. In this role, you will leverage your technical skills and functional expertise in P&L, balance sheet or regulatory capital (Basel 3) to build new calculations for the firm's books and records and for new regulatory capital rules released as part of Basel 3 Endgame. The position would provide a unique opportunity to drive one of the most impactful initiatives at the firm and to directly engage with colleagues and senior management across revenue areas, Risk, and Engineering.
Why join the team?

  • Broad exposure to pricing and calibration models for a variety of financial products, including derivatives, illiquid cash products, private equity, etc.
  • Exposure to challenging quantitative problems such as modeling risks for derivatives, large scale Monte-Carlo simulations of complete portfolios across the firm, fast and accurate approximate valuation risk measurements.
  • Exposure to machine learning and data science skills, and applications in finance.
  • Gain understanding of evolving regulatory framework and leverage quantitative skills to help the firm manage capital resources.
  • Interpersonal Communication: You'll engage with business users and engineers across all areas of the business to understand their requirements and to propose solutions tailored to their needs.
  • Autonomy: You'll have significant autonomy in designing and writing solutions to help our stakeholders deliver for the firm's clients.
  • Creativity: You'll be encouraged to suggest improvements to products and to propose ways in which we can add value for our stakeholders.
  • Training: Your manager will support your professional development, allowing you time for training at work, helping you learn and grow within the organization, and providing opportunities for increasing responsibility.

RESPONSIBILITIES AND QUALIFICATIONS

  • Develop quantitative models in 3 areas
    • Independent price verification models that govern key business strategies and decisions related to valuation of products including complex derivatives and hard to value private investments
    • Revenue analysis and modelling that governs new activity review, valuation adjustments and sign-off of daily P&L for all market making desks
    • Regulatory Capital models for key externally reported capital metrics that play a key role in determining forward-looking business strategies and decisions in an evolving regulatory landscape
  • Provide ongoing testing and support for existing models
  • Documentation and quality control of models
  • Work in a dynamic, fast-paced environment that provides exposure to all areas of Finance
  • Build strong relationships with business partners
  • Identify opportunities for cross-divisional collaboration and reuse of common solutions
  • Provide technical and functional guidance and leadership to junior members on a need basis

SKLLS AND EXPERIENCE WE ARE LOOKING FOR

  • PhD or Master's candidate in a quantitative field such as mathematics, physics, statistics or engineering
  • 4+ years experience in financial modeling
  • Excellent command of mathematics, modeling and numerical algorithms. Exposure to machine learning and data science skills, and applications in finance is a plus.
  • Strong programming skills and experience with an object oriented programming language (such as C++, Python, or Java)
  • Excellent communication skills including experience speaking to technical and business audiences and working globally
  • Comfortable with multi-tasking, managing multiple stakeholders and working as part of a team
  • Experience building pricing and risk models or familiarity with capital, stress testing and resolution planning


ABOUT GOLDMAN SACHS
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.

We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers .

We're committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more:https://www.goldmansachs.com/careers/footer/disability-statement.html

 The Goldman Sachs Group, Inc., 2023. All rights reserved.
Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Best UK Universities for Machine Learning Degrees (2025 Guide)

Explore ten UK universities that deliver world-class machine-learning degrees in 2025. Compare entry requirements, course content, research strength and industry links to find the programme that fits your goals. Machine learning (ML) has shifted from academic curiosity to the engine powering everything from personalised medicine to autonomous vehicles. UK universities have long been pioneers in the field, and their programmes now blend rigorous theory with hands-on practice on industrial-scale datasets. Below, we highlight ten institutions whose undergraduate or postgraduate pathways focus squarely on machine learning. League tables move each year, but these universities consistently excel in teaching, research and collaboration with industry.

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.