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Senior Data Scientist
Skills
Computer ScienceBalletCustomer ExperienceEnglishReadinessSalesStructured Finance
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 5+ years of experience in data science analytics applied ML or MLE in a high-growth environment
- Strong applied analytics and data science foundation including statistics experimentation causal thinking and forecasting
- Ability to scope ambiguous problems and drive decisions with stakeholders
- Comfort writing production-quality Python code and building maintainable internal systems
- Excellent communication for non-technical audiences
- High ownership and autonomy in a fast-paced environment
Nice to have
- Sales/GTM partnership
- Cloud analytics tooling
- Startup experience
- Structured systems thinking
Day to day
- Own data science end-to-end by turning ambiguous business questions into crisp scopes and decision-ready analysis.
- Build lightweight internal systems and tools so insights are reproducible maintainable and trusted by others.
- Partner closely with GTM product and finance leaders to shape questions surface anomalies and drive action from analysis.
Hiring process
- Intro call (30 min)
- Take-home exercise overview (30 min)
- Paid take-home (4-6 hours)
- On-site take-home review
- GTM collaboration
- Lunch with the team
- Problem solving discussion
- Systems and engineering discussion
- Culture interview
- References