Staff Data Scientist

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Data Scientist in the United States.

This role sits at the intersection of advanced machine learning, product strategy, and business impact, where you will act as a senior technical leader shaping how data science drives growth and operational excellence. You will tackle complex, ambiguous problems across customer acquisition, retention, forecasting, and optimization, translating them into scalable, production-ready ML solutions. The position requires someone who can move seamlessly between strategic thinking and hands-on execution, ensuring models are not only accurate but also robust and impactful in production. You will collaborate closely with Engineering, Product, and Finance teams to ensure data-driven decisions are deeply embedded into core business processes. This is a high-impact role where you will define technical standards, influence roadmaps, and mentor others while directly shaping key business outcomes. The environment is fast-moving, product-oriented, and highly data-driven, with a strong emphasis on measurable results and scalable systems.

In this role, you will lead the design, development, and deployment of machine learning systems that directly impact business performance and strategic decision-making. Your responsibilities include:

• Designing and building scalable ML systems and data products that drive growth, efficiency, and operational improvements across the organization.
• Translating ambiguous business challenges into clear technical roadmaps and data science solutions.
• Leading end-to-end development and deployment of production ML models, ensuring reliability, scalability, and integration into live systems.
• Partnering with cross-functional teams (Engineering, Product, Finance) to align data science initiatives with business priorities and key metrics.
• Defining and enforcing technical standards for model development, documentation, and reproducibility across the data science organization.
• Owning the full model lifecycle, from data design and training through deployment, monitoring, and long-term performance optimization.
• Communicating complex analytical and technical concepts clearly to technical and non-technical stakeholders, including leadership.
• Driving experimentation, forecasting, and optimization initiatives that improve business decision-making and resource allocation.

Requirements:

The ideal candidate is a seasoned data science leader with strong machine learning expertise and a proven ability to deliver production-grade systems with measurable business impact. You should be comfortable operating in ambiguous environments, influencing stakeholders, and balancing strategy with hands-on execution. Key qualifications include:

• 8+ years of experience in Data Science, Machine Learning Engineering, or related quantitative roles.
• Strong proficiency in Python and SQL, with deep experience in pandas, NumPy, scikit-learn, and at least one major ML framework (e.g., PyTorch, XGBoost, LightGBM).
• Proven experience building and deploying production ML systems with measurable business outcomes.
• Strong understanding of MLOps practices, CI/CD pipelines, and cloud environments (AWS or GCP).
• Excellent problem-solving skills with the ability to address complex, open-ended business and technical challenges.
• Strong communication and storytelling skills, with the ability to influence executive stakeholders without formal authority.
• Experience in forecasting, optimization, experimentation, or causal inference is highly preferred.
• Bachelor’s, Master’s, or PhD in a quantitative field (or equivalent practical experience).

Benefits:

• Competitive salary and equity compensation for full-time roles.
• Unlimited PTO, company holidays, and quarterly mental health days.
• Comprehensive health coverage including medical, dental, vision, and parental leave.
• 401(k) with employer matching contributions.
• Employee Stock Purchase Program (ESPP).
• Offsite team retreats and collaborative company events.
• Strong emphasis on wellness, flexibility, and work-life balance.