Top Data Science Jobs

The Data Scientist will build predictive models, design data pipelines, conduct analyses, and deploy solutions in a collaborative environment.

The Staff Data Scientist will identify AI opportunities, develop machine learning models, and provide mentorship while delivering business solutions using data analytics and AI technologies.

Technical lead for Growth Analytics: partner with Growth/Marketing/Sales to identify opportunities, design experiments and statistical models, build scalable measurement frameworks, mentor junior data scientists, translate business questions into analytic solutions, and communicate insights to drive acquisition, activation, retention, and reactivation.

Lead product analytics for in-vehicle experiences: define KPIs and instrumentation, perform deep-dive behavioral analyses, build dashboards and self-serve analytics, guide experimentation and causal inference, and mentor teams to scale analytics practices across the Vehicle Product organization.

As a Data Scientist, you will design and operationalize advanced analytics, develop scalable models, and collaborate with teams to enhance product capabilities in healthcare.

The Senior Associate, Data Scientist will partner with cross-functional teams to identify risks associated with models and validate machine learning models across the enterprise, enhancing decision-making while ensuring model governance and risk management.

The Senior Systems Data Scientist will develop methodologies for measuring trust in AV testing, manage data analysis frameworks, collaborate with teams, and provide insights for decision-making.

As a Principal Associate Data Scientist, you will develop credit underwriting models using machine learning and statistical methodologies, collaborate with cross-functional teams, and contribute to innovative modeling practices.

Build and validate predictive models, analyze large structured and unstructured datasets, generate business insights, present analytic results to stakeholders, and develop tools to advance analytics capabilities.

As a Staff Data Scientist at Gusto, you will drive data-informed decision-making, lead projects, collaborate with teams, and mentor others in statistical analysis and experimentation.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

Lead end-to-end direct mail marketing campaigns: define targeting and suppression logic, execute and validate data pipelines, manage offshore execution, measure ROI and experiment results, partner with marketing and third parties to optimize audiences and campaign performance, and present insights to senior leadership.

Perform data analysis supporting research, development, test, and evaluation of aircraft products and manufacturing processes. Select and validate algorithms, prepare and enhance data and models, and develop/test software in cloud environments to produce actionable engineering recommendations.

As a Data Scientist, you'll develop and validate machine learning models, implement AI solutions, and conduct fieldwork in support of customers.

The Senior Associate - Data Scientist will develop AI and machine learning solutions, focusing on model lifecycle management and delivering AI initiatives in collaboration with business teams.

Lead the Design of Experiments center of excellence, standardizing incrementality measurement, building testing infrastructure, and mentoring Data Scientists while optimizing customer experience and validating product initiatives.

Use advanced analytics, statistical methods, and machine learning to transform large datasets into actionable insights. Build data solutions and pipelines, perform exploratory analysis, create visualizations, validate models (including generative AI and NLP), collaborate with clients, mentor juniors, and maintain data quality to inform strategic decisions.

Lead data science initiatives within Data and Analytics Engineering to build predictive models, maintain data pipelines and lakes, apply ML/DL and generative AI, ensure data quality, coach teams, manage project timelines, and collaborate with stakeholders to drive data-driven business growth.

The AI/ML Data Scientist will develop and deliver innovative AI/ML solutions, train models, collaborate with business partners, and communicate findings effectively.

As a Data Scientist at Opendoor, you'll enhance pricing strategies through statistical models, machine learning, experiments, and interdisciplinary collaboration to drive business outcomes.

As a Data Scientist at SentiLink, you'll develop fraud detection models using machine learning, engage in product development, and support analysis across teams. This role emphasizes hands-on technical work and end-to-end project ownership in a fast-paced environment.

The Geospatial Data Scientist will automate data ingestion, analyze geospatial data, create visualizations, and ensure high-quality data workflows.

The Senior/Staff Data Scientist will build and deploy predictive models for consumer decisioning and business optimization, focusing on machine learning and statistical modeling. Responsibilities include model development lifecycle, data exploration, collaboration with teams, and improving product outcomes.

Build and validate predictive lending models, analyze consumer risk and portfolio impact, implement and monitor models with engineering, develop tooling and automated SQL/Python dashboards, design A/B tests, and communicate actionable insights to senior management.

Lead company-wide standards for causal inference and Bayesian experimentation. Build frameworks mapping evidence to actionable confidence levels, design learning strategies for high-impact questions, institutionalize Bayesian practices, partner with engineering to ensure reliable instrumentation, mentor data scientists, and serve as escalation point for complex measurement problems like interference, selection bias, and network effects.