Data Science Lead — Hands-on AI, Governance & Growth

Elliptic; Washington (District of Columbia); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Hybrid work arrangement

Comprehensive healthcare

Generous vacation and holidays

401k match

Job summary

Elliptic, a leader in digital asset intelligence, seeks a hands-on Head of Data Science to guide a small, growing team. You will own the team's direction, contribute code, and ensure robust model governance across collection, validation and deployment.

You will hire, mentor, and set strategic priorities within Elliptic's Intelligence function. Based in Washington, DC, you will partner with Product, Engineering, and Research to scale data capabilities, while staying technically active and

Qualifications

• Demonstrated AI/ML fluency and ability to apply tools in a data science workflow.
• Experience managing data scientists or ML engineers and delivering datasets or models.
• Experience hiring into a technical data team and defining bar for candidates.

Responsibilities

• Lead and grow Elliptic's data science team; set objectives and development paths.
• Hire data scientists; define job descriptions, plan, interviews and bars.
• Define data collection specs and ensure quality of datasets for model work.
• Own model governance: inventory, validation, drift monitoring, and production changes.

Skills

AI fluency

Team leadership

Hiring experience

Hands-on Python/SQL

Model governance

Cross-functional collaboration

Clear communication

DC relocation willing

US citizenship

Tools

Python

SQL

Spark/Databricks

AWS

Job description

Elliptic, a leader in digital asset intelligence, seeks a hands-on Head of Data Science to guide a small, growing team. You will own the team's direction, contribute code, and ensure robust model governance across collection, validation and deployment.

You will hire, mentor, and set strategic priorities within Elliptic's Intelligence function. Based in Washington, DC, you will partner with Product, Engineering, and Research to scale data capabilities, while staying technically active and