Skip to content
Staff Data Scientist – Identity & Attribution
| Company | Rokt |
|---|
| Location | New York, NY, USA |
|---|
| Salary | $250000 – $315000 |
|---|
| Type | Full-Time |
|---|
| Degrees | Bachelor’s |
|---|
| Experience Level | Senior, Expert or higher |
|---|
Requirements
- 8+ years of experience in ML, data science, or data engineering (or 4+ with a PhD), with a proven track record of delivering systems at scale.
- Expertise in Python and SQL, with hands-on experience building production-grade ML pipelines (e.g., Spark, Airflow, Kubeflow).
- Deep experience in one or more relevant domains: entity resolution, identity, fraud detection, attribution, or risk scoring.
- Strong grasp of experimentation design, causal inference, and the ability to translate analytical work into measurable business outcomes.
- Skilled at technical communication and cross-functional collaboration; able to operate in high-ambiguity, high-impact environments.
- Curious person who can solve problems with data, combining the skills of a data scientist, statistician, and data engineer.
Responsibilities
- Design and build scalable ML systems and data pipelines for identity resolution, attribution, and real-time user matching across billions of records.
- Lead end-to-end analytical projects, applying advanced ML/statistical techniques to uncover insights and drive product and revenue impact.
- Define metrics, design experiments (e.g., A/B testing), and ensure observability across identity system components to monitor health and effectiveness.
- Collaborate closely with product, engineering, and data stakeholders to set technical strategy and deliver business-critical improvements.
- Champion best practices in ML system design, code quality, and reproducibility, while mentoring peers and raising the team’s technical bar.
Preferred Qualifications
- Experience integrating third-party commercial data or working with user graph enrichment at scale.
