Software Engineer - Vice President - London - Controllers

Illinois CPA Society
London
2 months ago
Applications closed

Related Jobs

View all jobs

Software Engineer

Software Engineer

Software Engineer

Software Engineer

Software Engineer

Software Engineer (Junior)

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), measure and monitor the firm's capital, balance sheet and liquidity metrics, and regulatory filings across the globe.

OUR Impact:
Finance Engineering is responsible for designing and implementing solutions to manage the firm's P&L, measure and monitor 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 regulators for both regular business activity and under stress scenarios.

YOUR Impact:
Our team of engineers builds solutions to the most complex problems. We develop cutting-edge software and platforms that form the core of our key business and enable transactions to move in milliseconds. We provide real-time access to critical deal information and process billions of data points each day to inform firm-wide market insights and strategies. Team members have the opportunity to work at the forefront of technology innovation alongside industry leaders and make significant contributions to the field. This position provides a unique opportunity to gain subject matter expertise in both technology and finance, and to directly engage with colleagues and senior management from across the business, Risk, Finance, and Engineering.

Why join the team?

  • Tools & Technologies: You'll program in Java and model data using Alloy/Legend - a data management and data governance open source platform that we will teach you. Read more on Bloomberg . Other technologies in use in our space: RESTful services, Maven/Gradle, Apache Spark, BigData, HTML 5, AngularJs/ReactJs, IntelliJ, Gitlab, Jira.
  • Cloud Technologies: You'll be involved in building the next generation of finance systems onto the cloud platforms, one of the key strategies for the division in which you'll get exposure to technologies like AWS S3, Snowflake, EMR etc.
  • 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.
  • Interpersonal Communication: You'll engage with data producers and consumers across all areas of the business to understand their requirements and to propose solutions tailored to their needs.
  • 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.
  • Gain understanding of evolving regulatory framework and leverage quantitative skills to help the firm manage capital resources.
  • This role offers an excellent opportunity to learn and interact with a range of businesses and products across the firm.


RESPONSIBILITIES AND QUALIFICATIONSRESPONSIBILITIES

  • In an Agile environment manage end-to-end systems development cycle from requirements analysis to coding, testing, UAT, implementation and maintenance
  • Develop high level and detailed technical designs, testing strategies, and implementation plans
  • Work in a dynamic, fast-paced environment that provides exposure to all areas of Finance
  • Understand and respond to business needs, facilitating and developing process workflow, data requirements, and specifications required to support implementation
  • 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
  • Build and maintain key financial metric calculation models and associated infrastructure to support forward-looking business strategies and decisions in a evolving regulatory landscape
  • Work closely with a wide range of stakeholders globally, including Controllers, Risk, Operations, and various business units


SKLLS AND EXPERIENCE WE ARE LOOKING FOR

  • Bachelor's or Master's degree in Computer Science or related technical discipline
  • 5+ years of hands-on software development experience preferably in Java, C/C++, Python, competent in traditional (RDBMS) and modern datastores (NoSQL)
  • Strong programming and problem solving skills
  • A clear understanding of data structures, algorithms, software design and core programming concepts
  • Strong full-stack technical design and development skills and experience
  • Comfortable with multi-tasking, managing multiple stakeholders and working as part of a team
  • Excellent communication skills including experience speaking to technical and business audiences and working globally
  • Interest in finance

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.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.