Top Data Science Jobs

Lead applied research and engineering in data science and AI for cybersecurity: design experiments, build and deploy ML/LLM models, prototype solutions, co-author proposals, and present results to government sponsors and academic venues.

As a Senior Data Scientist at Databricks, you'll shape data science strategies, collaborate with stakeholders, mentor junior scientists, and build internal data products.

The Senior Data Scientist will design and deploy machine learning models, analyze complex datasets, develop analytical solutions, and mentor junior team members in a remote environment.

As a Senior Data Scientist at Waymo, you'll develop evaluation frameworks for performance metrics, analyze simulation and driving data, and mentor other data scientists while collaborating with engineering teams to enhance autonomous vehicle technology.

The Senior Data Scientist will analyze customer data, design experiments, build models, and support data-driven decision-making across product, marketing, and customer experience teams.

As a Senior Data Scientist, you will define AI evaluation frameworks, analyze educational data, and collaborate with cross-functional teams to ensure AI tools meet quality standards.

Lead development of data science models, mentor junior scientists, ensure data quality, and collaborate with stakeholders on requirements.

The Lead Data Scientist will enhance analytics through predictive modeling and data engineering, focusing on quality, feature generation, and continuous learning.

As a Senior Data Scientist at Omnissa, you will lead the data science team to innovate AI/ML solutions, develop advanced analytics models, and collaborate on integrating machine learning into core platform features.

Lead analytics to inform Finance and Product for the Fortnite ecosystem. Maintain core reporting and forecasting, build time-series models, develop shared data models, perform executive analyses, ensure data quality, support self-service pipelines, and collaborate cross-functionally to improve data-driven decision-making.

Lead analytics and forecasting for the Fortnite ecosystem: maintain core reporting, build time series forecasts and department-wide data models, perform executive analyses, ensure data quality, support self-service pipelines, and collaborate with engineering and product to drive data-driven decisions.

The Sr. Data Scientist will design and optimize intelligent search solutions using Elasticsearch and GenAI technologies, engaging with customers to implement effective AI-driven search strategies and improve decision-making outcomes.

As a Data Scientist at Wayve, you will generate actionable insights using causal methods and statistical frameworks to support AV product teams, focusing on complex data analysis and experimental techniques.

Design and implement quantitative behavior metrics for autonomous vehicles, build and maintain data pipelines and dashboards, analyze large-scale vehicle logs and simulation data to identify regressions, set metric thresholds to support geofence expansion, and communicate findings to technical and non-technical stakeholders.

The Senior Data Scientist leads data-driven initiatives, optimizing analytics for business decisions, mentoring staff, and ensuring data quality across healthcare projects.

As a Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.

Hands-on senior individual-contributor data scientist who builds, deploys, monitors, and maintains production-grade ML models (forecasting, regression, classification). Partners with investment and business stakeholders to translate ambiguous problems, deliver scalable MLOps solutions on cloud (GCP preferred), author reusable libraries, and raise engineering and modeling standards across the team.

Lead development of Vanta's business analytics function: build scalable product data assets, define measurement frameworks, use AI-assisted analytics, partner with cross-functional teams, and deliver executive-level recommendations to drive product and business decisions.

Lead analytics effort to collect, clean, integrate, analyze data and build/monitor predictive models (including recommendation systems). Partner with stakeholders, mentor data scientists, perform EDA, root cause analysis, and consult on analytics-driven strategies.

Lead end-to-end analytical design and validation for Signals, Forecasting, Simulation, Predictions, and Cohort Detection. Develop causal inference, time-series forecasting, survival/retention, and clustering methods; document assumptions and validation; partner with engineers to productionize models; ensure statistical rigor, significance correction, and trustworthy outputs that translate into clear product experiences.

Lead development of scalable analytic solutions that transform complex intelligence data into actionable insights. Design and implement data pipelines, automation, data models, visualizations, and production-ready Python tools. Provide technical leadership, rapidly prototype solutions, and collaborate with multidisciplinary IC teams to modernize analytic workflows and support operational decision-making.

The Principal Data Scientist will adapt complex statistical concepts for executive decision-making, lead communication standards within the data science organization, and represent Databricks at industry events. Responsibilities include mentoring, producing strategic insights, and advancing scientific methodologies.

Lead growth-focused data science initiatives, owning LTV prediction models across countries and channels. Translate business questions into models, analyze large customer and marketing datasets, evaluate acquisition quality, monitor and productionise models with engineering partners, and drive data-informed growth and retention decisions.

Lead ad-quality analytics: build data pipelines, dashboards, and automated reports; design and analyze A/B tests and causal inference studies; develop forecasting and modeling solutions; partner with product, engineering, and business stakeholders to translate findings into executive recommendations and drive ad product improvements.

Lead ad-quality and ad-product analytics: build pipelines, dashboards, and automated reports; design and analyze A/B tests and causal inference studies; develop models and alerts; translate findings into strategic recommendations for stakeholders and executives.