Top Senior Data Science Jobs

Build and own the analytics pipeline and semantic layer, define canonical product and business metrics, evaluate AI/agent performance, support pricing and profitability analysis, design dashboards and quality checks, translate ambiguous questions into analyses, and hire/scale the data team.

Provide analytics and data-driven insights for CoverMyMeds clients, prioritize work that drives commercial outcomes, build relationships with account teams, apply statistical and predictive methods, monitor portfolio health, deliver client-facing visuals and recommendations, support complex requests and escalations, and inform strategic decisions across product, analytics, and operations.

The Senior Data Scientist will analyze structured and unstructured data, build and maintain data pipelines, develop predictive and prescriptive models, and apply machine learning, NLP, forecasting, and statistical techniques. The role includes collaborating with data engineers, automating data processes, using cloud and distributed-data platforms, creating visualizations, communicating insights, and supporting digital transformation for a U.S. Special Operations Command program.

Build and deploy machine learning, predictive marketing, forecasting, and experimentation models. Develop scalable data pipelines, integrate diverse data sources, maintain data integrity, and deliver executive reporting insights. Analyze customer and market trends, support marketing measurement and product positioning, and translate complex technical findings into strategic recommendations. The role also involves mentoring junior staff and collaborating with IT to deploy analytical solutions.

Leads the development and deployment of advanced analytics, predictive models, AI and machine learning solutions. Builds data pipelines, prepares analytical datasets, monitors model performance, and operationalizes production-ready capabilities. Partners with business and technical teams to solve complex problems, communicate insights, establish governance practices, and deliver measurable outcomes. Provides technical leadership and mentorship while applying techniques such as forecasting, classification, clustering, NLP, generative AI, and LLMs.

Leads end-to-end data science solutions for retail and consumer clients, applying machine learning, statistical modeling, AI, and data wrangling. Frames business problems, develops and deploys production-grade models, communicates insights to stakeholders, ensures technical best practices, mentors team members, and supports business development through solution scoping, proposals, and presentations.

Leads the development and deployment of advanced analytics, AI, and machine learning solutions. Responsibilities include data preparation, pipeline development, predictive modeling, experimentation, model monitoring, generative AI applications, and production operationalization. Partners with business and technical teams, leads medium- to large-scale initiatives, mentors junior data scientists, communicates insights, promotes responsible AI, and delivers measurable business outcomes.

Leads technical support for VA healthcare AI citizen developers, developing and validating supervised, unsupervised, and reinforcement learning models. Builds synthetic healthcare data cohorts, designs secure cloud-based data science workflows, collaborates with federal stakeholders, interprets analytical results, mentors developers, and ensures model quality, documentation, privacy, governance, and regulatory compliance.

Lead end-to-end data science for a priority vertical (Insurance), building, validating, and deploying ML models that drive ROAS and lead quality. Partner with stakeholders and ML engineering to monitor live performance, iterate models, and identify new modeling opportunities to improve revenue and media efficiency.

As a Data Scientist Level 3, you will apply data science expertise to national security challenges, develop analytical tools, and communicate insights effectively to diverse audiences.

As a Data Scientist, Level 3, you'll leverage Python to automate workflows, perform data manipulation, and create visualizations, applying advanced analytics to complex datasets and communicating insights to varied audiences.

Analyze large-scale structured and unstructured data, develop and validate data models and methodologies, and perform large-scale parallel processing in clustered computing environments (ECL/HPCC, Python, C, SQL) to produce mission-relevant analytic products supporting Intelligence Community objectives.

As a Senior Data Scientist, you will lead data science initiatives, develop machine learning models, and collaborate with stakeholders to improve Perpay's products and financial health of customers.

As a Data Scientist at Anthropic, you'll support data-driven decisions across the customer lifecycle by defining metrics, analyzing data, and developing statistical models. You'll collaborate with various teams to influence strategies and improve analytics infrastructure.

As a Staff Data Scientist, you will address complex business challenges using AI and optimization algorithms, collaborate with engineering, define strategies, and implement data product frameworks.

The Data Scientist role involves developing measurement models, writing production-quality code in Python, and collaborating with teams to optimize data pipelines and ML workflows.

Deploy machine learning solutions for enterprise Oil & Gas customers, benchmarking against existing models and delivering measurable ROI. Responsibilities include data engineering, feature engineering, validation, model optimization, data leakage prevention, and secure last-mile integrations across cloud, on-premises, and air-gapped environments. The role partners with customers, sales, research, product, and solution architecture teams while translating technical insights into business value and product roadmap priorities.

Lead data science efforts by analyzing complex structured and unstructured datasets, developing algorithms and systems, and applying statistical and machine learning methods. Responsibilities include data cleaning, feature engineering, clustering, anomaly detection, trend analysis, and advising clients. The role also guides teammates, collaborates with clients, and translates data into actionable insights for public- and private-sector challenges.

Conduct statistical analyses on large structured and unstructured datasets; develop algorithms, visualizations, plots, and dashboards; and lead data science projects from scoping through delivery. Translate strategic questions into analytical solutions, communicate findings to technical teams and senior DoD leaders, respond to ad hoc requests, mentor junior scientists, and establish reproducible analysis practices. The role supports strategic decision-making, risk assessment, and campaign planning for Department of Defense clients.

Lead web and marketing analytics: define tracking specs, implement and validate scalable tracking, join web and game data, build dashboards and reports, deliver campaign-level insights, measure feature effectiveness, and partner with stakeholders to make data actionable.

Design, develop, and operationalize Python-based analytic pipelines and interactive dashboards integrating structured and unstructured data to support DoD/IC missions. Modernize legacy workflows for scalability and reproducibility, lead analysis and automated processes, and serve as a senior SME coordinating with clients on data-driven solutions in high-consequence environments.

Leads advanced analytics, machine learning, statistical modeling, and NLP solution development using healthcare and operational data. Builds scalable pipelines, visualizations, and deployed models on Google Cloud Platform, translates findings for clinical and executive leaders, designs experiments, and establishes performance metrics. Requires collaboration across clinical, technical, and data engineering teams, with occasional on-site travel for executive presentations.

Develop predictive models, quantitative analyses, visualizations, and data workflows using Palantir Foundry or Gotham. Analyze structured and unstructured data, transform siloed information into actionable intelligence, and advise national security clients on data-driven decisions. Collaborate with engineers, analysts, and mission stakeholders to solve complex programs and support mission-critical applications.

Leads Central Health System’s data science team and serves as its senior technical authority. Develops and validates predictive, machine learning, NLP, and forecasting models supporting population health, care management, and clinical decision-making. Oversees AI governance, model risk assessment, fairness, reproducibility, documentation, and regulatory alignment. Partners with clinical, data engineering, governance, and analytics teams while mentoring staff and managing advanced analytical standards across Epic, Azure, Snowflake, and other enterprise data sources.

Own product analytics across Axon’s ecosystem, partnering with product managers to define metrics, validate tracking, build durable data models, and deliver decision-focused analyses. Apply segmentation, experimentation, forecasting, and causal inference to product adoption and engagement questions. Help establish shared metric and reporting standards, maintain data quality and documentation, and explore AI agents for querying, anomaly detection, and insight generation.