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.
Designing and implementing metrics frameworks to measure product engagement, retention, and user behavior
Building statistical and machine learning models to understand user behavior and drive product decisions
Analyzing large-scale datasets to identify trends, anomalies, and actionable insights
Developing data pipelines and infrastructure to aggregate, transform, and prepare data for analysis
Conducting A/B tests and designing experiments to validate hypotheses and measure feature impact
Owning end-to-end analytical projects from problem scoping through implementation and monitoring
Building and deploying predictive models for forecasting, segmentation, and propensity scoring
Creating dashboards and visualizations to communicate findings to technical and non-technical stakeholders
Applying statistical rigor and causal inference methods to establish reliable measurement and evaluation frameworks
Implementing feature engineering pipelines to transform raw data into predictive signals for modeling
Building time series forecasting models to predict demand, usage, and capacity across business operations
Conducting deep-dive root cause analysis to identify performance bottlenecks and improvement opportunities
Building interpretable models that balance performance, explainability, and operational maintainability
Developing data quality frameworks and ensuring data governance across analytical systems
Applying optimization techniques and operations research methods to improve resource allocation and efficiency
Developing attribution and cost accounting models to allocate resources and understand financial impact
Architecting data systems and infrastructure that scale to support production analytics and autonomous agents
Designing evaluation frameworks and measurement methodologies for large-scale AI and ML systems
Building personalization and recommendation systems using behavioral data and machine learning
Designing novel methodologies for analyzing unique data characteristics and rare event estimation
Developing reinforcement learning models to optimize dynamic decision-making and resource allocation
Collaborating cross-functionally with product, engineering, and business teams to align on data-driven decisions
Translating ambiguous business questions into well-scoped analytical problems and hypotheses
Communicating complex analytical findings and recommendations to executive leadership and diverse stakeholders
Leading and mentoring data science teams while establishing analytical best practices and standards
Technology
The tools and technologies that define this role.
Open Jobs
55 open Data Scientist jobs across 22 companies.
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