Asset & Wealth Management - London - Vice President - Software Engineering London · United King[...] (Basé à London)

Jobleads
London
4 weeks ago
Create job alert

Asset & Wealth Management - London - Vice President - Software Engineering

Job Summary
Client Service Engineering is part of Goldman Sachs Asset Management; we are responsible for providing the technology that powers our award-winning client service organization. We operate as a full-stack team, and engineers contribute code in multiple languages on a variety of applications.

You will be part of our Investor Data team, which specializes in managing customer data and providing APIs for other teams to consume. You will work with groundbreaking technologies and apply large-scale computing, distributed systems, data pipelining, workflow orchestration, restful APIs, and statistical algorithm techniques to solve difficult problems. Our stack covers both AWS and on-prem deployments and is written in a variety of languages including Java (Spring), Scala, Python, and AWS Lambdas. To be successful, you will need to keep our long-term objectives in mind while delivering short-term features for our consumers. You should be comfortable with ambiguity and be open to identifying alternative paths. You will be as happy getting into code-level details as you are with coming up with a long-term technical vision and architecture for our applications.

Goldman Sachs Asset Management Division
Goldman Sachs Asset Management is one of the world’s leading asset management institutions. GSAM delivers innovative investment solutions, managing almost $3 trillion of our clients’ assets on a global, multi-product platform. In addition to traditional products (e.g. equities, fixed income, money market), our product offering also includes Hedge Funds, Private Equity, Fund of Funds, Quantitative Strategies, Fundamental Equity, and a Multi-Asset Pension Solutions Business.

Software is engineered in a fast-paced, dynamic environment, adapting to market and customer needs to deliver robust solutions in an ever-changing business environment.

Minimum Requirements

  • Master’s or bachelor’s degree in computer science, or related numerical/engineering field.
  • 5+ years professional experience in data processing and/or Data Mesh architectures.
  • Strong, self-motivated individual with analytical mindset who can multi-task to solve interesting and difficult technical problems under time pressure and resource constraints.
  • Adaptability and willingness to learn; open to contributing across the stack.

Preferred Qualifications

  • Experience with Java development and other programming languages; experience in Object Oriented analysis, design and testing best practices.
  • Knowledge of SQL and no-SQL databases (e.g. Mongo, Elastic).
  • Experience working with cloud; AWS, GCP, etc.
  • Excellent written and verbal communication skills, including experience working directly with both technical and non-technical stakeholders.

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 about our disability statement on our careers page.

Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity.

#J-18808-Ljbffr

Related Jobs

View all jobs

MA Operations -Financial Services Operations - Senior Manager

Head of Digital Engineering Service Portfolio (Basé à London)

Senior US Economist (Basé à London)

CX Data Suppot Officer

Liquid Fixed Income Fund Research – VP/SVP (Basé à London)

Engineering Manager

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.

Contract vs Permanent Data Science Jobs: Which Pays Better in 2025?

Data science sits at the intersection of statistics, machine learning, and domain expertise, driving crucial business decisions in almost every sector. As UK organisations leverage AI for predictive analytics, customer insights, and automation, data scientists have become some of the most in-demand professionals in the tech job market. By 2025, data scientists with expertise in deep learning, natural language processing (NLP), and MLOps are commanding top-tier compensation packages. However, deciding whether to become a day‑rate contractor, a fixed-term contract (FTC) employee, or a permanent member of an organisation can be challenging. Each path offers a unique blend of earning potential, career progression, and work–life balance. This guide will walk you through the UK data science job market in 2025, examine the differences between these three employment models, present sample take‑home pay scenarios, and offer strategic considerations to help you determine the best fit for your career.

Data Science Jobs for Non‑Technical Professionals: Where Do You Fit In?

Beyond Jupyter Notebooks Ask most people what a data‑science career looks like and they’ll picture Python wizards optimising XGBoost hyper‑parameters. The truth? Britain’s data‑driven firms need storytellers, strategists, ethicists and project leaders every bit as much as they need statisticians. The Open Data Institute’s UK Data Skills Gap 2024 places demand for non‑technical data talent at 42 % of all data‑science vacancies—roles focused on turning model outputs into business value and trustworthy decisions. This guide highlights the fastest‑growing non‑coding roles, the transferable skills many professionals already have, and a 90‑day action plan to land a data‑science job—no pandas required.

McKinsey & Company Data‑Science Jobs in 2025: Your Complete UK Guide to Turning Data into Impact

When CEOs need to unlock billion‑pound efficiencies or launch AI‑first products, they often call McKinsey & Company. What many graduates don’t realise is that behind every famous strategy deck sits a global network of data scientists, engineers and AI practitioners—unified under QuantumBlack, AI by McKinsey. From optimising Formula One pit stops to reducing NHS wait times, McKinsey’s analytics teams turn messy data into operational gold. With the launch of the McKinsey AI Studio in late 2024 and sustained demand for GenAI strategy, the firm is growing its UK analytics headcount faster than ever. The McKinsey careers portal lists 350+ open analytics roles worldwide, over 120 in the UK, spanning data science, machine‑learning engineering, data engineering, product management and AI consulting. Whether you love Python notebooks, Airflow DAGs, or white‑boarding an LLM governance roadmap for a FTSE 100 board, this guide details how to land a McKinsey data‑science job in 2025.