Data Scientist
Data Scientists in these roles build predictive and classification models that directly drive business outcomes, from revenue optimization and customer health scoring to autonomous vehicle performance evaluation and capacity planning. They distinguish themselves by owning problems end-to-end—from translating ambiguous stakeholder questions into measurable problems, through model development and validation, to production deployment and ongoing monitoring. These roles typically sit within cross-functional product, operations, or analytics teams at scale-up and enterprise AI companies, partnering closely with engineering, product, and business leaders to ensure models deliver sustained impact and reliability in real-world systems.
Skills
What companies are looking for in this role.
Defining key metrics and measurement frameworks to evaluate product performance and business health
Collaborating with cross-functional teams including product, engineering, and business stakeholders
Designing and implementing data models, pipelines, and infrastructure to support analytics and reporting
Communicating complex analytical findings and recommendations to non-technical stakeholders
Conducting exploratory data analysis to derive actionable insights and identify opportunities
Translating ambiguous business problems into measurable, quantifiable questions
Building and deploying predictive and classification machine learning models in production
Designing and executing rigorous experiments including A/B tests and causal inference studies
Monitoring model performance, detecting data drift, and maintaining production systems
Building time series forecasting models for demand, capacity, and resource planning
Feature engineering and data preparation for machine learning systems
Building measurement and orchestration frameworks for data pipelines and data quality
Analyzing user behavior, engagement, and retention patterns to drive product decisions
Optimizing business outcomes through pricing analysis, customer segmentation, and revenue modeling
Developing anomaly detection systems for infrastructure and performance monitoring
Evaluating and improving AI model quality, safety, and compliance capabilities
Designing self-serve analytics tools and data tooling for non-data users
Developing data-driven capacity and resource optimization models
Understanding AI-augmented workflows and measuring developer productivity in AI-assisted environments
Measuring and optimizing autonomous system performance and safety
Building agentic AI measurement and performance frameworks
Communicating effectively with diverse stakeholder groups from engineers to executives
Owning end-to-end problem solving from problem framing to deployment
Working across the full technology stack and collaborating closely with engineering teams
Balancing methodological rigor with speed and pragmatism in solution delivery
Building and scaling data science team culture and best practices
Championing data-driven culture and democratizing data access across organizations
Leading data science teams and mentoring junior data scientists
Technology
The tools and technologies that define this role.
Open Jobs
55 open Data Scientist jobs across 26 companies.
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