About the Company

The company is a fast-growing, well-funded fintech business focused on developing data-driven solutions for product and risk-related challenges. Its data team works closely with engineering and analytics professionals to apply statistical methods and machine learning to practical business questions.

About the Role

The company is seeking a Remote Data Scientist to join its small data team. This is a hands-on, non-client-facing role focused on using Python, SQL, applied statistics, and machine learning to investigate product and risk-related questions and generate useful insights. You will work closely with engineers and analysts, analyze data, and present findings to internal and external stakeholders. The position is open to candidates across the United States, with a preference for someone in the New York City area who can occasionally work in person.

Key Responsibilities

Apply Python and SQL to analyze data and address product and risk-related business questions. Use statistical methods, including hypothesis testing, regression analysis, and experimental design, to investigate data and support findings. Apply machine learning techniques using tools such as scikit-learn to solve practical problems. Collaborate with engineers and analysts on data analysis and related initiatives. Present analytical findings and insights to internal and external stakeholders.

Required Qualifications

Solid experience with Python and SQL. Foundational knowledge of statistics, including hypothesis testing, regression analysis, and experimental design. Exposure to applied machine learning techniques, such as those available through scikit-learn. Preferred Qualifications / Requirements Experience working at a startup or in a fast-paced team environment. Experience with statistical risk modeling. Salary & Benefits The salary range for this position is $150,000–$200,000, depending on experience (DOE). Location & Work Arrangement Remote position open to candidates located anywhere in the United States. The company is based in New York City and prefers candidates in the New York area who can occasionally work in person.