About The Position
Pagaya is a financial technology company reshaping the asset management space using machine learning and big data analytics to manage institutional money. With a focus on fixed income and alternative credit, Pagaya offers a variety of discretionary funds to institutional investors including pension funds, insurance companies, and banks.
Pagaya’s unique technology platform — Pagaya Pulse — runs on a suite of artificial intelligence technologies and state-of-the-art algorithms to deliver a consistently high and scalable performance edge. The company was founded in 2016 by seasoned finance and technology professionals with offices in New York and Tel Aviv.
The team manages over $3.2 billion in assets on behalf of institutional investors around the world. Pagaya just completed its financing rounds of over $100M led by a prominent sovereign wealth fundå
Pagaya is a fast-growing machine-learning-based fintech company. We’re looking for excellent engineers to join our Research team. If you love to tackle hard problems, you grasp algorithms quickly, you are enthusiastic about big data, you always think of the team and you are fun to work with – join us!
As a team member, you will work tightly with first-class researchers, design, and implement the whole machine learning life-cycle in the company. You will integrate new technologies and extend them to allow our researchers to execute data science tasks in scale and deploy our models into production quickly and safely. You will lead the engineering efforts of our huge research department (50 data scientists). The atmosphere in Pagaya is positive, young, and pragmatic.
- Excellent programming skills in Python
- 5 years of experience in programming
- Courage to tackle hard problems
- Analytical capability to learn fast and grasp complicated concepts
- Background in data-science / research Additional qualifications
- Knowledge in data-science technologies, such as:
- SageMaker, Dask / Spark, MLFlow / Trains etc., Prefect / Luigi / AirFlow etc., DVC, sklearn, pyarrow, etc.
- Experience with distributed computing
- Experience with containers infrastructure, such as ECS / EKS
- Scientific BSc (preferably computer science)