Senior Manager, Data Science

About the Role

This is a senior leadership role on a team tackling one of the hardest and highest-impact problems in blockchain analytics: connecting on-chain activity to real-world entities with precision and scale. You'll blend hands-on technical work with people management and product strategy, sitting at the intersection of blockchain intelligence, data science, and applied machine learning.

What You'll Do

• Lead and mentor a high-performing data science team, balancing individual execution with longer-term strategic vision.

• Drive technical innovation across a modern data stack (Python, Airflow, BigQuery, Kafka, Snowflake), ensuring pipelines and models scale with quality.

• Collaborate cross-functionally with engineering, product, and intelligence teams to turn raw blockchain data into actionable product insights.

• Set the standard for accuracy and trustworthiness in blockchain attribution, helping establish market-leading data quality.

• Recruit, develop, and retain top technical talent while growing the team's overall product and engineering maturity.

• Maintain a hands-on technical presence (~20–80 split), actively contributing code and technical direction rather than managing exclusively.

What We're Looking For

• 7+ years of data science experience, with at least 4 years directly managing data science or machine learning individual contributors.

• Prior hands-on experience as an MLE or data scientist — this is not a pure people-management role.

• Full-stack data science profile: strong proficiency in Python, statistical modeling, and data pipeline development (not analytics-only or BI-focused).

• Experience with large-scale data systems and orchestration tools such as BigQuery, Snowflake, Airflow, or equivalents.

• Demonstrated use of AI tools and LLMs to accelerate technical work and productivity.

• Background at a startup or hypergrowth company (Series A–C stage or equivalent).

• Experience in blockchain analytics, financial crime, fraud detection, or fintech data domains.

• Strong cross-functional collaboration skills across engineering, product, and intelligence stakeholders.

• Advanced degree (Master's or PhD) in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, or Engineering is a plus.

• U.S. work authorization required; no visa sponsorship available.

Compensation & Benefits

Base salary range: $210,000 – $230,000 USD annually. No visa sponsorship available.

Location

Fully remote within the United States. Primary location is Los Angeles, CA. Candidates must be U.S.-based with a minimum of 6 hours of daily overlap with the Eastern Time zone.