Core Engineering, Developer Experience Metrics, Quant Engineer, Associate/ Vice President, Singapore
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Overview
DEVELOPER JOURNEY STRATEGY AT GOLDMAN SACHS
The Developer Journey Strategy for the firm focuses on investing in the developer experience to minimize friction, promote standardization, and leverage artificial intelligence (AI) to enable seamless delivery.
By streamlining processes, implementing consistent practices, and integrating AI-driven tools and solutions, we empower developers to efficiently build and run products and platforms.
This strategy aims to enhance productivity, foster innovation, and ensure high-quality outcomes by providing developers with the advanced tools, resources, and support they need to succeed.
The incorporation of AI not only automates routine tasks and optimizes workflows but also provides predictive insights and intelligent recommendations, further enhancing the development process.
SDLC ENGINEERING
Part of Goldman Sachs’ Core Engineering group’s function is to provide best in class language support and tooling for our engineering community to facilitate the building, testing and deployment of their products.
We strive for our tooling to improve product quality, developer productivity and increase opportunities for collaboration.
Our aim is to innovate and drive technology solutions that will impact the bottom line for the firm.
By joining us, you will be part of a diverse global technical team focusing on solving critical business problems.
You will be working at the heart of the developer experience, ensuring the code that is written by thousands of GS engineers is versioned securely, reviewed expertly, compiled quickly, tested comprehensively, and distributed widely.
What You Will Be Working On
We are seeking a highly skilled and motivated Quantitative Engineer to join our team at Goldman Sachs.
This role is focused on analyzing developer lifecycle data, especially generative AI usage, and building logical models to measure and enhance developer productivity.
The ideal candidate will be responsible for modelling solutions that provide insights and generate key metrics such as code quality, code generation frequency, production incidents, test coverage, and other relevant indicators.
The successful candidate will work closely with cross-functional teams to ensure that data analysis and models created provide insights and trends across our suite of developer lifecycle products, ultimately driving improvements in productivity across the organization.
We look for creative collaborators who evolve, adapt to change and thrive in a fast-paced global environment.
Key Responsibilities
Data Analytics & Regression: Conduct in-depth data analytics and regression analysis on the firm's engineering and Dev AI data to uncover insights, identify trends, and quantify the benefits of generative AI tooling on engineering productivity.
Cross-Correlation and Impact Assessment: Cross-correlate data across various datasets to comprehensively assess the impact of Dev AI on KPIs such as code quality (defect density, code coverage, technical debt) and operational stability (deployment frequency, mean time to recover, change failure rate).
Model Refinement and Development: Continuously refine existing analytical models used to measure engineering productivity and the efficacy of current tools.
Develop new data models and analytical frameworks as new generative AI tools and technologies are integrated into the engineering workflow, ensuring robust and accurate measurement of their impact.
Ad-hoc Data Analysis: Perform timely and accurate ad-hoc data analysis to address specific, urgent business questions and provide rapid insights to support immediate decision-making.
Skills And Experience We Are Looking For
5+ years (Associate) / 10+ years (VP) of experience in data modeling skills – physical and relational data modeling
Strong industry experience in a data engineering or data science role
Strong scripting ability in one or more languages (e.g. python, scala, bash)
Ability to analyze and translate developer data into analytical models
Problem solver with attention to detail who can see complex problems in the data space through end to end
Comfortable managing multiple stakeholders, driving consensus, and influencing outcomes, strong problem solving and analytical skills
Strong oral and written communication skills
Preferred Qualifications
BSc / MSc in relevant field (Computer Science, Data Science, or related field)
Experience with implementing data strategies and converting logical models into physical data model
Experience with AI and machine learning technologies
Experience working with large and disparate datasets
Experience with SQL and optimizing queries
Experience designing, implementing, and maintaining ETL and data flow processes in an enterprise environment
What’s In It For You
Be part of the team continually innovating on measurement of AI in the developer space
Work with advanced AI technologies to enhance coding efficiency, productivity and developer experience
Be part of a forward-thinking team that values continuous improvement and ensures high-quality results
Stay updated with the latest technological advancements and best practices by engaging with industry leaders and vendors
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 are 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:
The Goldman Sachs Group, Inc., 2024.
All rights reserved.
Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Engineering and Information Technology
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