Senior/Staff Data Scientist
New
S
SignalFireVenture Capital Startups
Remote - No PreferenceFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years of experience in data science, applied statistics, machine learning, decision science, or a related field
- Required Skills
- PythonSQLMachine LearningData scienceA/B testingR
Requirements
- 5+ years of experience in data science, applied statistics, machine learning, decision science, or a related field
- Strong proficiency in Python, R, SQL, or similar analytical languages
- Experience with statistical modeling, experimentation, causal inference, forecasting, or predictive analytics
- Track record of using data to influence product strategy, customer outcomes, or business performance
- Ability to work with large, complex, and imperfect datasets
- Experience partnering closely with product managers, engineers, operators, and executive stakeholders
- Experience developing models or analytical systems that are used in production or operational decision-making
- Strong judgment around methodology, measurement, tradeoffs, and uncertainty
- Experience in venture-backed startups or rapidly scaling technology companies preferred
- Advanced degree in statistics, economics, computer science, mathematics, operations research, or a related field preferred
Responsibilities
- Partner with product, engineering, and business leaders to identify high-impact opportunities for data science
- Design and analyze experiments to evaluate product changes, growth initiatives, and operational strategies
- Develop predictive, forecasting, recommendation, ranking, or optimization models
- Apply statistical methods and causal inference techniques to measure impact and inform decisions
- Build metrics, analytical frameworks, and dashboards that improve visibility into product and business performance
- Translate complex analyses into clear recommendations for technical and non-technical stakeholders
- Collaborate with engineers to productionize models and integrate data science into customer-facing products
- Identify patterns in user, customer, operational, and market data
- Establish best practices for experimentation, model evaluation, data quality, and analytical rigor
- Mentor other data scientists and help shape the company’s data strategy and tooling
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