Quantitative Engineer, Digital Lifecycle Advice-New York-Associate-Asset & Wealth Management

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.

Engineering, which is comprised of our Technology Division and global strategists groups, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Start here.

• dynamic asset allocation methodologies for retirement investing (a.k.a. think glidepath and personalized glide path construction for Defined Contribution 401(k) participants)
• strategic asset allocation model construction and robust algorithms related to "on-the-fly" active risk budgeting given various constraints and inputs without human intervention
• financial planning methodologies such as forecasting using capital market assumptions and spend down retirement income strategies under IRS taxation schedules, different account types (pre-/post-tax, Roth) and guaranteed income products with actuarial background knowledge.
• The field of application in the area of digital lifecycle advice is vast and a changing project-based specialization/focus will be required with a holistic product thinking in mind. This position will be situated within our Multi Asset Solutions Research Strategists (using internal proprietary software language (Slang) similar to Matlab/C++, Python, Matlab) and work in close collaboration with our tech engineer teams on Java/Ruby proprietary applications.

• Dynamic Personalized Portfolio Advice for Retirement Goal considering various Investor Characteristics, Market Factors and other financial advice aspects.
• Risk-based Portfolio Advice considering various Investor Characteristics, Market Factors, Risk Characteristics, quantitative model-driven portfolio methodologies and backtesting, and Investor Suitability and other financial advice aspects.
• Investment Management and Portfolio Construction with active risk management.
• Planning Methodology considering Human Capital Factors inspired by labor economics, IRS rules and plan specific requirements, account type level requirements, actuarial modeling, taxation methodology, stochastic forecasting methodology, and other financial planning aspects.

• Enhancing and maintaining existing and creating new advice and financial planning methodology solutions, and design specifications in concert with our team of financial engineers and financial/investment analysts that are aligned with and implementable from an Investment Solutions point of view and are maintainable from a risk management perspective to deliver products that meet or exceed our high expectations.
• Designing, and improving algorithmic model outcomes, including documentation of design specifications.
• Developing tools to improve automated functionality for monitoring, portfolio construction, and research processes
• Scoping and work estimation of new advice and financial planning methodology solutions such as but not limited to retirement income, liability driven investing in an algorithmic, scalable way.
• Working with software designers and developers to ensure effectiveness of advice and financial planning methodology solutions in production software.
• Working with software developers to ensure advice and financial planning methodology solution aspects are implemented correctly in user-facing software.
• Working with compliance to support the need to comply with rules and regulations faced by financial services companies.
• Working with the business development team to create content for use in sales pitches and client meetings.
• Documenting and/or presenting the Advice group's work for internal and external audiences.

• Advanced Degree in Computer Science, Operational Research, Applied Mathematics or Quantitative Finance/Economics, ideally with strong and relevant specialization in Finance. PhD preferred.
• 3 years of experience in the financial advice industry, knowledge of the regulatory framework. - CFP, FRM, CFA, CIPM charterholders preferred.
• Strong software engineering skills, ability to understand, extend and debug complex code.
• Comfortable and thrive in a fast-paced, entrepreneurial environment.
• Strong interpersonal skills, team-oriented, and collaborative.
• Excellence in algorithmic analysis and structuring of complex problems, ability to communicate ideas on paper and present to internal and external stakeholders and clients in an intuitive and easily understandable way.