About the Role
We are looking to expand our data science organization by adding a Senior Data Scientist dedicated to exploring the uncharted space of quantitative asset-backed lending practices. In addition, you will be solving a variety of interesting problems in creating a better experience for retail investors, promoting capital-raising efficiency and bringing prosperity for all.
In this role, you will be both a researcher and an engineer. On the research front, you will be exploring the space of macroeconomics, consumer lending, retailer investor behavior etc.; you will also be identifying and leveraging existing and alternative data sets and applying advanced analytics and algorithms to extract market insights and trends to help drive company’s investment and strategy decisions. On the engineering front, you will be prototyping and iterating data-driven product features that improve user experience and reduce operational burden of the enterprise. You will also be collaborating closely with engineering partners to productionize it into the platform, which touches the day-to-day financial decisions of hundreds of thousands of retail investors.
What you'll do:
- Identify relevant and valuable alternative data assets and partner with our data engineers to build and optimize data pipelines to ingest, transform, standardize and loan them into the data warehouse
- Conceptualize, prototype and iterate machine learning algorithms and product features in order to improve the user experience of our platform and bring efficiency to the operation
- Partner with our engineering team to productionize and integrate the feature into our system
- Research macroeconomics trends, assumptions and forecasts with alternative data sets to drive competitive advantages in the asset-backed lending practice
- Analyze consumer lending products and collateral and extract critical insights in advising strategic, business-critical decisions
What you'll need:
- PhD (preferred) or equivalent experience with a stellar track record in a quantitative field e.g. computer science, statistics, applied math or related field
- 3+ years of experience in developing predictive models and statistical analyses in a product-centric environment
- Strong proficiency in SQL and Python and/or R
- Ability to quickly pick up new technology and grasp concepts in a new domain
- Comfort in exploring in uncharted and undefined spaces while staying focused on the end goal for the business
- Strong experience with credit quantitative analysis in financial services (preferred)
Yieldstreet is building the largest global digital wealth management platform to change the way wealth is created. With an investor-first approach, our investor community builds a diversified portfolio of investments outside of the stock market to generate passive income. Yieldstreet is giving unprecedented access to asset classes such as Real Estate, Marine, Legal, Art & Commercial. We’re headquartered in New York City with offices in Brazil, Argentina, Malta and Greece.
We offer an attractive market compensation and benefits package including a competitive base salary, bonus opportunity, stock option plan, health, dental & vision benefits, life insurance, 401(k) match, unlimited paid vacation, sabbatical and paid holidays and that's before you even step in the office!
This is an opportunity to work with a group of diverse, smart, and friendly people from 8 different countries who speak a total of 17 different languages. Our team is comprised of successful entrepreneurs with combined exits of over $1B, and we get social with each other during happy hours, exercise classes and team off sites in our work hard/play hard culture. We're located in a beautiful new office in Midtown, our building is close to most major subway lines.
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