Help Shape the Future of Finance
Pagaya is a financial technology company working to reshape the lending marketplace, for investors, by using machine learning, big data analytics, and sophisticated AI-driven risk analysis. With its current focus on consumer credit and real assets, PAGAYA’s proprietary suite of solutions and pipelines to banks, fin-tech lenders and others was created to actively find greater value for institutional investors. PAGAYA’s models create additional value to that pipeline as well, by increasing liquidity and, in turn, increasing opportunities for access to credit.
We move fast and smart, identifying opportunities and building end-to-end solutions from AI models and unique data sources to new business partnerships and financial structures. Every PAGAYA team member is solving new challenges every day in a culture based on collaboration and community. We all make an impact regardless of title or position.
The company was founded in 2016 by seasoned finance and technology professionals, and we are now 400+ strong in New York, Tel Aviv, and LA. The team manages over $4.5 billion in assets on behalf of institutional investors around the world. You will be surrounded by some of the most talented, supportive, smart, and kind leaders and teams—people you can be proud to work with!
- Continuous Learning: It’s okay to not know something yet, but have the desire to grow and improve.
- Win for all: We exist to make sure all participants in the system win, which in turn helps Pagaya win.
- Debate and commit: Share openly, question respectfully, and once a decision is made, commit to it fully.
- Lead and develop a team of 4-5 Data Scientists, helping them advance their careers
- Working side-by-side with managers from various disciplines on the day to day – Software Developers, Machine Learning Engineers and Data Analysts.
- Design solutions for the company’s core mission using Data Science methodologies from various domains
- Responsible for developing new cutting edge algorithms based on various Machine Learning techniques
- Generate and test working hypotheses in unexplored territory
- Track record of excellence, being the “Go to” person in your previous team.
- Relevant Working Experience (Algorithms Researcher, Data Scientist, ML Engineer) – at least 3 years.
- Scientific Degree graduate with an honored BSc or MSc.
- Good applied statistics skills, such as distributions, statistical testing, regression, etc.
- Proficient in Python and the Data Science Stack.
- Managerial experience – Strong Advantage
- Knowledge in some of the following can be an advantage: machine learning, predictive modeling, optimization, risk and finance