Data Science Lead
Elliptic helps businesses detect and prevent financial crime in crypto through blockchain analytics and compliance solutions.
Funding history
Investors
About Elliptic
Elliptic provides blockchain analytics tools for financial institutions, crypto businesses, and regulators to manage risk and investigate crime. Their platform enables real-time wallet screening, transaction monitoring, and cross-chain investigations to ensure regulatory compliance and prevent financial crime.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead and grow a data science team while remaining hands on with coding, research, and technical review. You will set objectives, manage performance and development, hire data scientists, and define the team's priorities. You will build data collections and compliance capabilities, oversee model governance and remediation, guide research and experiments, and partner across functions to deliver reliable platform capabilities.
Requirements
- Demonstrated experience managing data scientists or machine learning engineers
- Experience hiring into a technical team
- Deep hands-on data science and machine learning capability
- Strong Python and SQL skills
- Experience interrogating large behavioural or transactional datasets
- Experience delivering datasets, models, or capabilities from ambiguous questions
- Experience with a cloud data lake, Spark or Databricks, and AWS
- Clear communication with technical and non-technical stakeholders
- Based in Washington, D.C. or willing to relocate
- US citizenship
- Ability to apply and critically evaluate AI tools and approaches in data science workflows
Responsibilities
- Lead, manage, and grow the data science team
- Set team objectives, manage performance, and create development plans
- Own the end-to-end hiring process for data scientists
- Define, sequence, and deliver data collections for compliance work
- Own model inventory, validation, testing, monitoring, governance, and issue remediation
- Frame research questions, run experiments, and recommend capability priorities
- Write code and review technical methods
- Own the reliability and trade-offs of clustering, attribution, heuristics, and labelling work
- Partner across Intelligence, Engineering, Product, Research, and Investigations
- Set and enforce AI usage and verification standards for the team
Benefits
- Hybrid working, including the option to work from almost anywhere for up to 90 days per year
- $650 home office budget
- 25 days of annual leave plus 8 US public holidays
- An additional birthday leave day
- 16 weeks of fully paid eligible parental leave
- Medical, dental, and vision coverage with premium contributions for employees and dependents
- 401k company match
- Access to Spill mental health support
Hiring Process
Dedicated interview stage assessing AI fluency using the candidate's own tooling.