Data Scientist (Senior/Staff) - VC Backed Startups
About The Position
Join SignalFire’s Talent Network for Senior/Staff Data Scientist Roles at VC-Backed Startups. This is not an application for a specific job, but a way to get on the radar of VC-backed startups that are actively hiring Data Science talent. SignalFire partners with top early-stage startups across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS. We are looking to connect with exceptional Senior and Staff Data Scientists who are excited about using data, experimentation, and machine learning to solve complex product and business problems at high-growth startups. By joining SignalFire’s Talent Network, your profile will be shared with our portfolio companies, giving you visibility into exclusive early-stage opportunities that may not be publicly listed.
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
- Strong communication skills and the ability to explain technical findings clearly
- Experience developing models or analytical systems that are used in production or operational decision-making
- Strong judgment around methodology, measurement, tradeoffs, and uncertainty
Nice To Haves
- Experience in venture-backed startups or rapidly scaling technology companies may be preferred
- Advanced degree in statistics, economics, computer science, mathematics, operations research, or a related field may be preferred, but is not always required
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 raise the technical standard of the broader data organization
- Help shape the company’s data strategy, tooling, and long-term analytical roadmap
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
