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**Real Estate Data Science, Vice President** - Lead data science & AI initiatives for London-based Real Estate investing platform - Bridge investment, AI, analytics; translate investment questions into actionable solutions - 5+ years in quantitative fields; strong Python, SQL skills; experience in real estate, infrastructure, private equity, or similar domains **Responsibilities:** - Lead data science for Real Estate investing platform - Partner with deal teams to identify high-value AI opportunities - Translate investment questions into analytical problems & outputs - Develop data-driven models, tools, and AI solutions - Evaluate & leverage alternative & traditional datasets - Collaborate with portfolio companies on data & AI initiatives **Qualifications:** - MSc, PhD, or equivalent in quantitative discipline - Proven data science, machine learning, & AI skills - Deep statistical modelling & experimental design knowledge - Experience leading analytics initiatives & influencing cross-functional teams - Comfortable operating in fast-paced, dynamic environments - Valuable: real estate, private equity experience & AI technologies familiarity **About Goldman Sachs** - Leading global investment banking, securities & investment management firm - Committed to diversity, inclusion & equal opportunity

Compensation: Not specified
City: London
Country: United Kingdom

Full Job Description

Real Estate Data Science, Vice PresidentLondon, Greater London, England, United Kingdom

Opportunity Overview

CORPORATE TITLEVice President

OFFICE LOCATION(S)London

JOB FUNCTIONQuantitative Engineering

DIVISIONAsset & Wealth Management

Role Overview

Join the Alternatives Data Science team and lead data science and AI initiatives across the Real Estate investing platform. The role sits at the intersection of investing, AI, and analytics, partnering closely with Deal Teams, portfolio company management teams, and Engineering to identify opportunities where data and AI can improve investment decisions and drive value creation.

A key aspect of the role is acting as the bridge between investment professionals and technical teams, translating investment questions into analytical solutions and ensuring data science and AI outputs are communicated in a commercially relevant and actionable way.

The Alternatives Data Science team works alongside Goldman Sachs Deal Teams and asset management teams across the full investment lifecycle.

Key Responsibilities

Serve as the Data Science lead for the Real Estate investing platform, supporting origination, due diligence, asset management, and value creation activities.
Partner with Deal Teams to identify high-value opportunities where data science, AI, and advanced analytics can enhance investment decision-making and operational performance.
Translate commercial and investment questions into well-defined analytical problems and communicate technical outputs coherently to non-technical stakeholders.
Lead the development of data-driven models, decision-support tools, and AI-enabled solutions across the investment lifecycle.
Identify, evaluate, and leverage traditional and alternative datasets to generate investment insights and support underwriting, market analysis, asset monitoring, and value creation initiatives.
Partner with portfolio company management teams to identify and implement data and AI initiatives that drive measurable business outcomes.
Scale the bespoke analytics to be applicable to the broader investment sectors so that the solutions can be redeployed periodically.
Stay current with developments in AI, machine learning, and data science, helping drive adoption of new capabilities across the investment platform.

Qualifications, Experience & Attributes

MSc, PhD, or equivalent degree in Mathematics, Statistics, Economics, Engineering, Computer Science, Data Science, Operations Research, or a related quantitative discipline.
5+ years' experience applying data science, machine learning, AI, or advanced analytics to solve complex commercial problems with measurable business impact.
Strong programming skills in Python and SQL, with experience building robust analytical solutions and working with large and complex datasets.
Deep understanding of statistical modelling, machine learning, predictive analytics, and experimental design.
Demonstrated experience working directly with senior business stakeholders, translating commercial requirements into analytical solutions and communicating technical findings to non-technical audiences.
Experience leading analytics initiatives from problem definition through implementation and business adoption.
Proven ability to influence decision-making and drive adoption of data-driven solutions across cross-functional teams.
Strong stakeholder management, communication, and problem-solving skills.
Comfortable operating in a fast-paced, dynamic environment with multiple stakeholders and competing priorities.

Highly Valued

Experience within real estate, infrastructure, private equity, investment banking, consulting, or other data-intensive commercial environments.
Experience supporting investment, strategy, underwriting, capital allocation, pricing, or operational decision-making through advanced analytics.
Experience leveraging alternative data, geospatial data, market intelligence, forecasting, or predictive analytics to generate commercial insights.
Hands-on experience with modern AI technologies, including LLMs, prompt engineering, RAG architectures, agentic workflows, embeddings, and AI-enabled productivity solutions.
Experience building analytical products, decision-support tools, or AI applications that have influenced strategic, operational, or investment outcomes.
Familiarity with modern cloud data platforms and technologies, including Databricks, Snowflake, AWS, Azure, or GCP.
Experience working in embedded, investment-facing, consulting, or front-office analytics teams where business adoption and impact are critical measures of success.
Familiarity with responsible AI practices, model governance, and evaluation frameworks.

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.

Were 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

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.

We Offer Best-In-Class Benefits

Healthcare & Medical Insurance

We offer a wide range of health and welfare programs that vary depending on office location. These generally include medical, dental, short-term disability, long-term disability, life, accidental death, labor accident and business travel accident insurance.

Holiday & Vacation Policies

We offer competitive vacation policies based on employee level and office location. We promote time off from work to recharge by providing generous vacation entitlements and a minimum of three weeks expected vacation usage each year.

Financial Wellness & Retirement

We assist employees in saving and planning for retirement, offer financial support for higher education, and provide a number of benefits to help employees prepare for the unexpected. We offer live financial education and content on a variety of topics to address the spectrum of employees priorities.

Health Services

We offer a medical advocacy service for employees and family members facing critical health situations, and counseling and referral services through the Employee Assistance Program (EAP). We provide Global Medical, Security and Travel Assistance and a Workplace Ergonomics Program. We also offer state-of-the-art on-site health centers in certain offices.

Fitness

To encourage employees to live a healthy and active lifestyle, some of our offices feature on-site fitness centers. For eligible employees we typically reimburse fees paid for a fitness club membership or activity (up to a pre-approved amount).

Child Care & Family Care

We offer on-site child care centers that provide full-time and emergency back-up care, as well as mother and baby rooms and homework rooms. In every office, we provide advice and counseling services, expectant parent resources and transitional programs for parents returning from parental leave. Adoption, surrogacy, egg donation and egg retrieval stipends are also available.

Benefits at Goldman Sachs

Read more about the full suite of class-leading benefits our firm has to offer.

Learn More

Full Job Description

Real Estate Data Science, Vice PresidentLondon, Greater London, England, United Kingdom

Opportunity Overview

CORPORATE TITLEVice President

OFFICE LOCATION(S)London

JOB FUNCTIONQuantitative Engineering

DIVISIONAsset & Wealth Management

Role Overview

The Alternatives Data Science team works alongside Goldman Sachs Deal Teams and asset management teams across the full investment lifecycle.

Key Responsibilities

Serve as the Data Science lead for the Real Estate investing platform, supporting origination, due diligence, asset management, and value creation activities.
Partner with Deal Teams to identify high-value opportunities where data science, AI, and advanced analytics can enhance investment decision-making and operational performance.
Translate commercial and investment questions into well-defined analytical problems and communicate technical outputs coherently to non-technical stakeholders.
Lead the development of data-driven models, decision-support tools, and AI-enabled solutions across the investment lifecycle.
Identify, evaluate, and leverage traditional and alternative datasets to generate investment insights and support underwriting, market analysis, asset monitoring, and value creation initiatives.
Partner with portfolio company management teams to identify and implement data and AI initiatives that drive measurable business outcomes.
Scale the bespoke analytics to be applicable to the broader investment sectors so that the solutions can be redeployed periodically.
Stay current with developments in AI, machine learning, and data science, helping drive adoption of new capabilities across the investment platform.

Qualifications, Experience & Attributes

MSc, PhD, or equivalent degree in Mathematics, Statistics, Economics, Engineering, Computer Science, Data Science, Operations Research, or a related quantitative discipline.
5+ years' experience applying data science, machine learning, AI, or advanced analytics to solve complex commercial problems with measurable business impact.
Strong programming skills in Python and SQL, with experience building robust analytical solutions and working with large and complex datasets.
Deep understanding of statistical modelling, machine learning, predictive analytics, and experimental design.
Demonstrated experience working directly with senior business stakeholders, translating commercial requirements into analytical solutions and communicating technical findings to non-technical audiences.
Experience leading analytics initiatives from problem definition through implementation and business adoption.
Proven ability to influence decision-making and drive adoption of data-driven solutions across cross-functional teams.
Strong stakeholder management, communication, and problem-solving skills.
Comfortable operating in a fast-paced, dynamic environment with multiple stakeholders and competing priorities.

Highly Valued

Experience within real estate, infrastructure, private equity, investment banking, consulting, or other data-intensive commercial environments.
Experience supporting investment, strategy, underwriting, capital allocation, pricing, or operational decision-making through advanced analytics.
Experience leveraging alternative data, geospatial data, market intelligence, forecasting, or predictive analytics to generate commercial insights.
Hands-on experience with modern AI technologies, including LLMs, prompt engineering, RAG architectures, agentic workflows, embeddings, and AI-enabled productivity solutions.
Experience building analytical products, decision-support tools, or AI applications that have influenced strategic, operational, or investment outcomes.
Familiarity with modern cloud data platforms and technologies, including Databricks, Snowflake, AWS, Azure, or GCP.
Experience working in embedded, investment-facing, consulting, or front-office analytics teams where business adoption and impact are critical measures of success.
Familiarity with responsible AI practices, model governance, and evaluation frameworks.

About Goldman Sachs

We Offer Best-In-Class Benefits

Healthcare & Medical Insurance

Holiday & Vacation Policies

Financial Wellness & Retirement

Health Services

Fitness

Child Care & Family Care

Benefits at Goldman Sachs

Read more about the full suite of class-leading benefits our firm has to offer.

Learn More

Real Estate Data Science, Vice President

Full Job Description

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