AI & Emerging technologies

Data Science Lead

Elliptic

London · Greater London · United Kingdom

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

Reference: WJ-747_31171320 · Posted 01 Nov 2026

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