Finance Engineering- Corporate Treasury Data Scientist - Analyst - Bengaluru
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.
Who We Look For
Goldman Sachs Engineers are innovators and problem-solvers, building solutions in risk management, big data, mobile and more. We look for creative collaborators who evolve, adapt to change and thrive in a fast-paced global environment.
In Finance Engineering, you'll find an exciting confluence of computer science, finance and mathematics being used to solve for what our shareholders would like from us - a high return for the right risk taken.
The Corporate Treasury Data Science team is looking for world class data scientists and data analysts to work closely with Corporate Treasury partners to employ quantitative analytics to drive optimizations of firm liquidity, cash and collateral management, funds transfer pricing and trade execution strategies. This is an integrated group which both explores new ideas for optimizing the funding management of the firm and also executes data engineering functionality, all in one team.
Corporate Treasury lies at the heart of Goldman Sachs, ensuring that businesses have the appropriate level of funding to conduct their activities, while also optimizing the firm's funding costs and managing liquidity risks. As part of the Corporate Treasury Data Science team you will be exposed to securities division and banking initiatives, to new business activities, and to critical strategic programs Goldman Sachs pursues to maintain its leadership among global financial institutions.
Corporate Treasury Data Scientists use their scientific background and engineering talent to implement machine learning, quantitative analytics and management solutions in software. Corporate Treasury Data Science endeavors include guiding funding sourcing decisions, allocation of financial resources, quantification of funding costs, and strategies to minimize costs and hedge risks. Successful data scientists are highly analytical, driven to own commercial outcomes, and communicate with precision and clarity.
Corporate Treasury Data Science team welcomes applicants with a Masters or a PhD in financial engineering/financial math; quantitative sciences, e.g. physics, statistics, applied math or other quantitative discipline; or relevant professional experience. Strong analytical skills, mathematical fluency, working knowledge of machine learning algorithms, and programming abilities are required.
RESPONSIBILITIES AND QUALIFICATIONS
How you will fulfill your potential:
- Develop data science models and analytics to further Corporate Treasury's firmwide mandates: liquidity risk and interest rate risk management and trade execution, cash & collateral management, funding optimization
- Use machine learning techniques and statistical modeling to develop pricing analytics and behavioral models for deposit products
- Optimize the firm's liability stack by developing balance sheet analytics and hedging strategies
- Work with treasury, desk strategists, and technology departments to implement processes to optimally leverage financial resources to achieve commercial priorities
- Perform quantitative analysis and facilitate business understanding of technical results
- Use experience in building linear and non-linear models to develop analytics to drive the growth of the deposit platform
Skills and experience we are looking for:
- Expertise in quantitative analysis, e.g. statistics, stochastic calculus, scientific computing, econometrics, machine learning algorithms, financial modeling
- Strong software design experience
- Solid background in Hadoop, Spark and Python in order to carry out large scale financial or technical computations
- Familiarity with financial markets and assets, with a preference for experience with asset pricing and metrics used to govern financial institutions, e.g. liquidity coverage ratios, balance sheet and capital ratios
- Excellent communication skills, including experience speaking to technical and business audiences and working globally
- Can apply entrepreneurial approach and passion to problem solving and product development
- Up to 3 years of relevant, continuous experience
ABOUT GOLDMAN SACHS
The Goldman Sachs Group, Inc. is a leading global investment banking, securities and investment management firm that provides a wide range of financial services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in all major financial centers around the world.
© The Goldman Sachs Group, Inc., 2019. All rights reserved Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Vet.
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