Data Scientist (Senior/Staff) - VC Backed Startups at Signalfire — Remote

# Join SignalFire’s Talent Network for Senior/Staff Data Scientist Roles at VC-Backed Startups

🛑 This is not an application for a specific job. Instead, this is a way to get on the radar of VC-backed startups that are actively hiring Data Science talent. If you have any questions, please direct inquiries to talentnetwork@signalfire.com.

We’re 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.

## Who Should Join?

We’re looking for data scientists who are:

✔ Passionate about using data to improve products, customer outcomes, and business decisions ✔ Experienced in experimentation, statistical analysis, predictive modeling, or causal inference ✔ Excited to work closely with product, engineering, operations, and business teams ✔ Comfortable operating with incomplete data and ambiguous problems in fast-moving startup environments ✔ Interested in building scalable analytical frameworks, models, and decision-making systems

## Typical Roles & 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

## Common Qualifications

While each startup has its own hiring criteria, many Senior and Staff Data Scientist roles in our network look for:

• 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
• 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

## 💡 Technologies You Might Work With:

• Languages & Analysis: Python, R, SQL, pandas, NumPy, SciPy
• Modeling & Machine Learning: scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow
• Experimentation & Statistics: A/B testing, causal inference, Bayesian methods, time-series analysis
• Data Platforms: Snowflake, BigQuery, Redshift, Databricks, Spark
• Visualization & Analytics: Looker, Tableau, Mode, Hex, Amplitude
• Workflow & Development: Jupyter, dbt, Airflow, Git, Docker, cloud platforms

## What Happens Next?

• Submit your application to join SignalFire’s Talent Ecosystem.
• We review applications on an ongoing basis to identify strong candidates.
• If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.
• No match yet? We’ll keep your profile on file for future Senior and Staff Data Scientist roles across our portfolio.