Top Data Science Jobs

Own complex data science projects applying machine learning, generative AI, statistical methods, and natural language processing to legal knowledge management and regulatory intelligence. Build systems for retrieval, summarization, classification, requirements extraction, impact analysis, and decision support. Establish data foundations, evaluation metrics, human-review workflows, and responsible AI practices while partnering with legal, policy, research, engineering, and business stakeholders. Mentor practitioners and operationalize scalable, auditable solutions.

Leads the design, development, deployment, and monitoring of advanced statistical and machine learning models for insurance pricing, underwriting, claims, fraud, retention, and growth. Advises executives and actuarial teams, establishes modeling and experimentation standards, ensures responsible and scalable productionization, and mentors data scientists. The role also advances MLOps, AI infrastructure, model lifecycle management, explainability, fairness, and data science strategy.

Develop scalable data pipelines, algorithms, and AI systems using large datasets. Build and optimize machine learning, deep learning, generative AI, and agent-based models for business automation and decision-making. Translate technical findings into actionable recommendations, collaborate across product and engineering teams, mentor data professionals, and influence AI and analytics roadmaps.

Internship role to develop and deploy user-growth algorithms: user segmentation, recommendations, LTV/churn/conversion models, A/B testing, causal inference analyses, and collaborate with product and engineering to drive measurable growth.

Develops and validates cell-culture bioprocess models, simulations, automation, digital twins, and machine-learning solutions. Leads technical workstreams, prototypes scalable digital tools, analyzes production data, evaluates emerging technologies and customer use cases, and transfers validated concepts into product development pipelines. The role also represents scientific expertise externally and collaborates across technical, commercial, and application teams to accelerate industrialization.

Build, validate, deploy, monitor, and maintain predictive models and analytical reports. Translate findings for technical and non-technical stakeholders, promote data literacy, deliver training, collaborate on data infrastructure, apply advanced statistical and machine learning methods, and support analytical requests across mental health and crisis care programs.

The Data Scientist will collaborate with teams to shape product strategy using machine learning and econometric models on large datasets, measuring outcomes and designing data-driven solutions.

The Data Scientist will conduct data research, develop analytics models, ensure data quality, and communicate actionable insights to stakeholders. Responsibilities include statistical analysis, data mining, and collaboration with business experts to enhance decision-making.

The Data Scientist Level 3 will analyze large datasets, develop strategies for data extraction, and communicate findings. Required experience includes machine learning and programming.

Analyze large marketing datasets, build predictive models for segmentation, pricing, and demand forecasting, support targeted campaigns and retention, partner with product and marketing, apply statistical and ML methods, ensure data quality with engineering, and communicate insights to stakeholders to drive conversion and retention improvements.

Lead end-to-end data science projects: define problems, build/test hypotheses, deliver scalable solutions for productization. Perform advanced statistical and time-series analyses, collaborate cross-functionally, and translate insights into customer value while supporting deployment and system optimization.

Lead design and implementation of scalable workflows to transform large geospatial/intelligence data into mission-ready analytic products. Script in Python, produce operational visualizations, provide senior-level direction and QA, and collaborate across NGA and IC to support intelligence operations.

The Data Scientist will develop performance evaluation frameworks for autonomous vehicles, using statistical models and metrics to ensure quality and safety of the Waymo Driver, while collaborating with engineering teams on simulation data and product readiness.

Seeking a QlikView/Java expert with over 10 years of experience in data visualization and model development using QlikView. Responsibilities include dashboard creation, data integration, and administration of QlikView tools.

The Data Scientist at GenLogs will build machine-learning systems, analyze large datasets, and collaborate with engineering and product teams to deliver advanced logistics intelligence solutions.

The Data Scientist will build AI-driven fraud and risk systems, work with real-world data, and leverage graph techniques to improve detection and labeling. They will partner with engineering to scale data systems in the compliance domain.

The Data Scientist will analyze claims data, develop predictive models, and work with unstructured data using R and Python in a financial services context.

Partner with Marketing as the embedded data science lead to build marketing measurement, attribution, LTV/ROAS/CAC models, run experiments, analyze the full funnel, create forecasts and dashboards, and influence channel strategy and budget allocation.

Seeking a Data Scientist with expertise in Full stack Development and AWS Architecture for a 3-6 month local project.

The Data Scientist will analyze data using machine learning and statistical methods to deliver insights, develop algorithms, and support customers with analytical discussions.

Conduct analyses on complex healthcare data to showcase new technologies and process improvements, using statistics and machine learning techniques to enhance decision-making and patient outcomes.

Lead end-to-end data science initiatives across pay TV, digital products, media sales, and customer lifecycle. Design, deploy, monitor ML/AI solutions (churn, propensity, personalization, recommendation, forecasting), partner with stakeholders, build data pipelines, run experiments (A/B, uplift), mentor teams, and translate analytics into measurable commercial impact.

The Staff Data Scientist will lead data science projects, build ML models, develop AI solutions, and mentor junior staff while integrating data-driven insights into business operations.

As the Staff Data Scientist, you will lead the data science function, driving strategy, mentoring peers, and shaping product direction through advanced analytics and experimentation.

The Bioinformatics Data Scientist will analyze multi-omics data, develop methods, build tools, and communicate findings to support drug development decisions.