Data Science Lead

Elliptic • Washington, PA

1d • $144,000 - $260,000 • Hybrid

About The Position

Elliptic is a leader in digital asset decisioning, providing a comprehensive platform for extracting crypto data and intelligence across blockchains. Founded in 2013 and headquartered in London, Elliptic has offices in New York, Washington D.C., UAE, Singapore, and Tokyo. This role offers the opportunity to lead a data science team on an industry-unsolved problem, while remaining hands-on with coding. The position focuses on building the data foundation for compliance in the context of autonomous agents and seeks a values-led company environment where a small team is trusted with commercially significant questions.

The Data Science Lead will be instrumental in leading data science within Elliptic's Intelligence team, working alongside Intelligence Collection, Research and Investigations, and Professional Services. This is a player-coach role with the potential for team scaling. Initially, the lead will manage a small team of data scientists, owning the team's direction, performance, and growth. Responsibilities include owning the evidence for models built by the team and representing them at Elliptic's model risk governance forum. The role emphasizes that this is not a mere compliance add-on but is central to the trust institutions place in Elliptic's outputs. The need for a lead stems from adding more data scientists to a team tackling an unsolved problem, requiring someone with intrinsic domain understanding rather than just management oversight. The lead will define the team's focus, lead hiring efforts, and be a trusted technical resource.

Requirements

• AI fluency, including applying AI tools and approaches within a data science workflow (coding, data exploration, pipeline acceleration, task automation) and critically evaluating AI output.
• Demonstrated experience managing data scientists or machine learning engineers, including setting objectives, owning performance, and developing people.
• Experience hiring into a technical team, including defining the hiring bar.
• Deep, hands-on data science and machine learning capability that is current.
• Strong Python and SQL skills, with the ability to interrogate large behavioral or transactional datasets.
• A track record of taking ambiguous questions to delivered datasets, models, or capabilities, including defining 'good enough'.
• Experience with a modern data stack comparable to Elliptic's: cloud data lake, Spark or Databricks, and AWS.
• Clear communication with technical and non-technical stakeholders.
• Ability to cascade direction to a team so individuals understand the importance of their work.
• Based in Washington, D.C. or willing to relocate there.
• US citizenship.

Nice To Haves

• Work on agentic systems, LLM agents, or autonomous transaction flows in compliance, payments, fraud, or infrastructure.
• Experience building a large dataset or collection from scratch, including schema decisions, quality checks, and maintenance.
• Blockchain or on-chain data experience (clustering, attribution, heuristics, anomaly detection, mempool analysis, privacy-preserving systems research).
• Experience in payments, fraud, or risk data science where the cost of a false negative is commercial.
• Experience growing a team from a few people to a full department.
• A PhD or equivalent research training, or a record of published applied research.
• Experience in a regulated environment or with model risk management frameworks (financial services, or as a vendor, or other domains with equivalent assurance requirements).

Responsibilities

• Lead and grow the data science team, setting objectives, owning performance and development, and managing difficult conversations.
• Level the team against Elliptic's Intelligence career framework and build development paths.
• Own the end-to-end hiring process for new data scientists, including defining the hiring plan, interview panel, and bar.
• Build the data collection for the future of compliance, defining standards, sequencing work, and setting quality bars.
• Own model governance for the team's models, including maintaining the model inventory, ensuring validation and testing evidence, monitoring for drift, and managing remediation of issues.
• Lead Elliptic's data science work by framing research questions, running experiments, and forming defensible views to present to leadership.
• Stay technically hands-on by writing code, reviewing team's work at a methodological level, and making critical method calls.
• Own the team's existing commitments, including work on clustering, attribution, heuristics, and labeling, ensuring reliability and managing trade-offs.
• Partner with cross-functional teams (Intelligence Collection, Collection Engineering, Research and Investigations, Chief Scientist, Product, and Engineering) to ensure data science work translates into usable platform capabilities.
• Set the AI working standard for the team, defining its use in engineering and research workflows and ensuring verification processes.

Benefits

• Hybrid working (up to 90 days per year from almost anywhere)
• $650 remote work budget
• $1,000 annual Learning & Development budget
• 25 days of annual leave + 8 US Public Holidays
• Birthday Leave
• 16 weeks fully-paid enhanced parental leave (regardless of gender or path to parenthood)
• Comprehensive medical, dental, and vision coverage
• Company match for 401k
• Full access to Spill mental health support

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed