Data Science Lead

Overview

Lead the data science function within Elliptic’s Intelligence team, guiding a growing team to solve unsolved industry problems. You will own model governance, drive data collection and dataset quality, and partner across functions to deliver platform-scale capabilities. This role combines hands-on coding with strategic leadership to shape the future of compliance analytics. Your work will impact how institutions rely on AI-driven insights to fight financial crime.

Pay / Benefits

• Hybrid working
• Remote working budget
• Learning & Development budget
• Holidays: 25 days + bank holidays; birthday off
• Enhanced parental leave (16 weeks fully-paid)
• Private health insurance (Bupa)

Responsibilities

• Lead and grow the data science team, setting objectives aligned with company strategy and delivering development plans.
• Own end-to-end hiring for the data science team, including role definitions, interviewing, and onboarding.
• Define data collection requirements, translate directives into data specifications, and establish quality standards for future compliance datasets.
• Maintain and govern models: inventory, validation, drift monitoring, remediation, and production change reviews with proper artefacts.
• Frame research questions, run initial experiments, and present defensible recommendations to leadership.
• Stay hands-on: contribute code, review methods, and guide technical direction.
• Oversee existing commitments (clustering, attribution, heuristics, labelling) and manage trade-offs for reliability.
• Collaborate with cross-functional teams to deploy data science as platform capability rather than isolated analysis.
• Set the AI working standard for the team and ensure verification within engineering and research workflows.

Key requirements

• AI fluency with demonstrable application in data science workflows (coding, data exploration, pipeline/model work)
• Experience managing data scientists or ML engineers: setting objectives, performance management, and people development
• Experience hiring into a technical team, including defining hiring bars
• Deep, hands-on data science and ML capability with Python and SQL; ability to interrogate large datasets and defend methods
• Proficiency with a modern data stack (cloud data lake, Spark/Databricks, AWS)
• Clear communication to both technical and non-technical stakeholders; ability to cascade direction to a team
• Based in Washington, D.C. or willing to relocate; US citizenship
• Track record delivering datasets, models, or capabilities from ambiguous questions

• Strong communication with stakeholders
• Accountability for outcomes and difficult conversations
• Pragmatism in balancing rigour and speed
• Python
• SQL
• Spark

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