A growth-stage company building AI-powered blockchain intelligence to expose and stop financial crime.
Senior Manager, Data Science
This is a leadership role inside a 400-person organization that has raised significant capital and works with government agencies, financial institutions, and crypto platforms to root out fraud, sanctions evasion, and illicit digital-asset activity. You will guide a team of data scientists and machine learning engineers who build production-grade models and heuristics that surface bad actors across multiple blockchains—work that moves from research to real-world enforcement in days, not quarters. The team depends on a modern stack (Python, Airflow, Kafka, Snowflake) and a deep partnership with engineering to shape data products that are fast, explainable, and mission-critical. You will set the technical direction, mentor senior individual contributors, and collaborate closely with product, engineering, and intelligence analysts to turn terabytes of on-chain data into decisive investigative advantage.
What they're looking for
- 7+ years of experience in data science or applied machine learning, with at least 2 years managing high-performing teams in a production environment.
- Proficiency in Python and familiarity with data infrastructure tools such as Airflow, Kafka, and Snowflake; comfort with Git-based workflows.
- A track record of shipping models and data products that solve tangible, high-stakes problems—experience in fraud detection, financial crime, cybersecurity, or trust & safety is a strong plus.
- Clear point of view on how to balance exploratory research with pragmatic delivery, and the communication skills to align technical work with company and customer priorities.
- Comfortable working in a distributed environment across U.S. time zones; role is open to candidates in New York, San Francisco, or fully remote.