Top Data Science Jobs

The Data Scientist will design and develop advanced analytics applications, employing machine learning and statistical techniques to interpret complex datasets and improve operational effectiveness.

The Principal Data Scientist - Oncology will lead efforts in standardizing and connecting biomedical and clinical data through the development of scalable knowledge graph infrastructure and AI-Ready datasets.

As a Data Scientist, you will design and develop data pipelines, perform data analysis, and collaborate with the product team to implement solutions for large datasets.

The Data Scientist will develop AI-driven simulation models, analyze data, and work closely with engineers and customers to improve engineering decisions and solutions.

The Data Scientist will develop AI-driven simulation tools, analyze data, create predictive models, and integrate solutions with engineering teams while collaborating closely with customers.

The Data Scientist will develop predictive models, design experiments, translate data insights, and collaborate across teams to enhance member experiences and drive strategic decisions at BECU.

As a Data Scientist III, you'll build customer identity systems, develop recommendation models, predictive analytics for customer behavior, and collaborate with ML Ops and Data Engineering.

As a Data Scientist at Booz Allen, you'll analyze and manipulate data, develop models, and provide insights using various data science techniques and tools, including machine learning and data visualization.

As a data scientist, you will analyze complex data sets, develop algorithms, and collaborate with clients to inform their decision-making processes.

Produce actionable insights through statistical analysis, experimentation, and behavioral modeling to optimize lifecycle marketing, segmentation, pricing, and monetization. Partner with stakeholders, Analytics Engineering, and ML teams to define data foundations, design A/B tests, build propensity and scoring models, document learnings, and mentor junior analysts. Incorporate agentic analytics to automate recurring analyses.

Lead a data science team to build predictive models, perform large-scale data analysis, collaborate with stakeholders and engineering to deploy models, manage projects, and translate insights into business recommendations.

Design and implement advanced data science and ML models across online experience, marketing, merchandising, and store operations. Build scalable data models and pipelines, evaluate data quality, create visualizations, collaborate with cross-functional teams, and productionize analytics using reusable code and best practices.

Lead end-to-end data science within R&D: extract and analyze clinical and operational data, build and validate advanced ML/AI and LLM-integrated solutions, translate insights for stakeholders, mentor teams, and drive product innovation for Invisalign.

Design, deliver, and maintain revenue-optimizing analytics and optimization products. Identify commercial opportunities, build models (forecasting, RL, optimization), process large/unstructured data, coordinate stakeholders and IT, implement end-to-end solutions, and support Analytics team development.

Lead development of time-series and econometric models (ARIMA, VAR, state-space, WLS, panel data) and Bayesian probabilistic frameworks. Use causal inference and stochastic processes to produce actionable insights, work with large datasets on Databricks, communicate results to stakeholders, and mentor junior team members.

Lead a small-to-medium data science team to design, develop, and deploy advanced AI/ML solutions (especially LLMs/Transformer models), mentor junior staff, define methodologies and governance, collaborate cross-functionally, and set team strategy and high standards for model development.

Design and build scalable data pipelines and models to enable segmentation, attribution, real-time engagement, and analytics. Ensure data quality, governance, and GDPR/PII compliance while partnering with MarTech, analytics, and marketing teams to deliver production-ready datasets, event streams, and CDP functionality for customer journey orchestration.

Design and deploy predictive risk and segmentation models for commercial insurance underwriting and pricing. Apply actuarial principles, statistical and ML techniques, manage large datasets, validate and monitor models, and translate analytical outputs into actionable insights for product and underwriting teams.

Lead data science efforts for sustainment systems: design data pipelines and models, perform statistical analysis, build interactive dashboards, maintain VMs/databases, collaborate cross-functionally, mentor teams, and establish data governance and quality practices for Triton Enterprise.

Transform analytical models into interactive GEOINT visualizations and analyst-facing interfaces, streamline production workflows, identify trends and insights, and operationalize geospatial data using Python, SQL, GIS tools, version control, and dashboarding frameworks to support mission-critical NGA/USSOCOM operations.

Lead advanced data analysis and modeling efforts to solve business problems. Develops complex statistical models and algorithms, ensures data quality, identifies new data sources, and partners with leadership to implement model results into operations. Presents findings and recommendations to technical and executive audiences and mentors junior staff.

As a Data Scientist in the Innovation Team, you'll develop machine learning algorithms on molecular sequencing data to enhance cancer diagnostics and treatment, collaborating with diverse experts on high-impact projects.

The Data Scientist will analyze complex data sets, build models for strategic recommendations, and collaborate with business teams to enhance website personalization and product recommendations.

The Senior Data Scientist will oversee experiment design and analysis for user migration initiatives, collaborating with cross-functional teams and utilizing advanced statistical methods for decision-making.

Lead experimentation in user migration and marketing strategies, applying advanced statistical techniques and causal inference methods to drive business decisions.