Top Data Science Jobs

Own end-to-end data science for growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; generate actionable insights; and influence product, growth, finance, and operations leaders. The role requires strong SQL or Python skills, independent analytical problem-solving, clear communication, and ownership of ambiguous, high-impact initiatives.

Build knowledge bases and extraction pipelines for generative AI/ML research. Develop metadata, annotation, provenance, and reproducible dataset workflows; analyze experimental, simulation, and evaluation data; create dashboards and reports; validate structured knowledge; and support research documentation and coordination with academic subcontractors.

Analyzes structured and unstructured datasets supporting U.S. Navy electronic warfare systems. Develops statistical, machine learning, NLP, data modeling, visualization, and reporting solutions to improve system readiness, reliability, maintainability, operational availability, and lifecycle performance. Integrates logistics, engineering, maintenance, and operational data; identifies trends and risks; and presents data-driven findings to technical and program stakeholders.

Develops analytical models and applications for U.S. Navy electronic warfare and sustainment systems. Applies data mining, statistical analysis, NLP, machine learning, and data modeling to structured and unstructured data. Integrates logistics, engineering, maintenance, reliability, and operational data to assess readiness, performance, risks, and availability. Creates visualizations, dashboards, reports, and briefings, while collaborating with engineers, logisticians, operations researchers, and program personnel to support lifecycle management and data-driven decisions.

Analyze complex structured and unstructured datasets to answer customer questions and support informed decisions. Apply data science, machine learning, statistics, data mining, and graph algorithms; gather and interpret data; develop analytical solutions; and communicate findings. The role requires programming, SQL, and Secret clearance, with preferred experience in analytical tools such as R, Tableau, SAS, SPSS, and AWS.

Support model risk governance by maintaining policies, documentation, inventories, validation plans, training, and stakeholder communications. Develop statistical programs and analytical solutions using R, Python, SQL, Hive, Spark, and cloud platforms to analyze large datasets and support credit risk and business intelligence consulting engagements.

Own product and business analytics across experimentation, causal inference, instrumentation, KPI reporting, pricing, advertising, subscriptions, and conversion. Design experiments, analyze event-level consumer data, partner with engineers on telemetry, and communicate recommendations using statistical rigor. The role also supports thought leadership, manages an independent analytics roadmap, and informs product and business strategy.

Leads development of statistical and machine learning models for time-series, geospatial, kinematic, and radar data. Responsibilities include feature engineering, forecasting, anomaly detection, data integration, ETL, visualization, algorithm evaluation, simulation, dataset creation, and stakeholder communication. The role also contributes to mission-focused software applications, APIs, data pipelines, documentation, code reviews, and agile development while requiring an active Top Secret or CBP/DHS suitability clearance.

Develop and deploy advanced machine learning and data science solutions across large numeric and textual datasets. Partner with data scientists, engineers, and product managers to build customer-focused products. Lead model design, training, evaluation, validation, and implementation while researching emerging technologies and translating complex analyses into business outcomes.

Lead end-to-end generative AI and machine learning initiatives, designing scalable and secure AI architectures and developing predictive, prescriptive, optimization, NLP, deep learning, and multimodal models. Analyze healthcare datasets, conduct experiments and A/B tests, evaluate emerging approaches, optimize production systems, and translate findings into executive-level recommendations. The role also emphasizes responsible AI, including fairness, transparency, and accountability.

As a Senior Data Scientist, the role involves leveraging data analysis, experimentation, and statistical methods to influence business decisions and enhance Gusto's product performance, while mentoring team members.

Develop and deploy production-grade AI, machine learning, and generative AI solutions for insurance business challenges. Responsibilities include building LLM applications, prompt engineering, RAG workflows, data pipelines, experiments, proof-of-concepts, and scalable AI systems. The role involves monitoring model performance, generating business insights, collaborating with stakeholders, and communicating technical findings to diverse audiences.

Develops data science models, analytical processes, visualizations, dashboards, and reports for U.S. Navy electronic warfare systems. Integrates logistics, engineering, maintenance, reliability, and operational data to evaluate system readiness, reliability, maintainability, performance, risks, and lifecycle sustainment. Applies data mining, statistical analysis, NLP, and machine learning to support operational decisions and collaborates with engineers, logisticians, analysts, and program personnel.

Data Scientist I will support Sportsbook and Casino commercial strategy through advanced analytics, machine learning, personalization, promotion engines, and lifetime value modeling. Responsibilities include analyzing player behavior, developing segmentation and LTV models, conducting experiments and causal analyses, collaborating with stakeholders and data teams, and delivering data-driven recommendations. The role requires strong Python, SQL, statistics, experimental design, and machine learning skills, with iGaming, customer lifetime value, or generative AI experience preferred.

Analyze SQL data using Python or R to identify trends, test statistical significance, and solve business problems. Present insights and recommendations to stakeholders, often collaborating with data engineers. Create visualizations in Tableau, adapt analytical approaches to business needs, and work within Agile teams and sprint-based delivery cycles.

Analyze federal workforce data and position descriptions using statistical modeling, NLP, machine learning, and text analytics. Develop dashboards, visualizations, and reports; map duties and skills to job series and grade levels; validate findings with HR professionals and leadership; and provide recommendations supporting accurate, compliant job classification and reclassification decisions.

Designs and implements machine learning models, data-mining methods, advanced analytical algorithms, statistical analyses, artificial intelligence solutions, and data-analysis software. The role requires extensive experience developing descriptive, predictive, and prescriptive analytics, analyzing datasets, and performing software or cloud development. An active TS/SCI clearance with polygraph is required, along with a quantitative degree or qualifying equivalent experience.

Design, develop, deploy, and maintain AI and machine learning models, pipelines, and data-driven solutions across Honeywell business groups. Define data acquisition strategies, apply statistical and data science methods, integrate models into operational platforms, and help govern analytics and AI/ML capabilities for the Forge platform. Collaborate with data scientists, engineers, and architects in a global team.

Develop and deploy AI and machine learning models, pipelines, and data-driven solutions across Honeywell business groups. Define data acquisition strategies, apply data science methods, support analytics strategy and governance, and integrate models into operational platforms. Collaborate with data scientists, engineers, and architects while advancing MLOps, deep learning, NLP, and AI capabilities for the Forge platform.

Leads experimentation, causal inference, advanced statistical analysis, machine learning, and scalable data-product development. Partners with product, engineering, and research teams to generate insights, identify opportunities, influence executive decisions, and shape product strategy. Owns cross-functional projects, analytics roadmaps, reporting, stakeholder adoption, and methodological standards while translating complex data into actionable business outcomes.

Owns experimentation, business analytics, reporting, and advanced analysis for Realtor.com’s RDC Next platform. The role analyzes consumer and agent behavior, designs A/B and quasi-experiments, builds trusted datasets and dashboards, and delivers recommendations that influence product and business strategy. It also develops AI-enabled analytics workflows using LLMs, RAG, and agentic tools; partners with Product, Engineering, Finance, Marketing, and data teams; mentors analysts; and helps establish analytical standards and scalable data solutions.

Leads Responsible AI data science initiatives by developing and validating AI testing protocols, automating analyses with Python, identifying PII and PHI vulnerabilities, and designing red-team scenarios for conversational AI. The role documents responsible AI practices, supports governance and regulatory compliance, communicates findings to legal, compliance, and technical stakeholders, and mentors colleagues. It requires expertise across traditional machine learning, generative AI, agentic techniques, AI ethics, fairness, and the full AI lifecycle.

Leads product analytics, experimentation, and advanced analyses for consumer content and visualization experiences. Defines success metrics, designs tests, improves tracking and data quality, builds ETL pipelines and AI-enabled self-service reporting, and translates consumer behavior insights into product and business strategy. Partners with Product, Engineering, Finance, and data teams to identify opportunities, measure performance, and influence the product roadmap.

Senior analytics partner leading product experimentation, business analytics, consumer behavior analysis, and performance measurement for content and visualization experiences. Responsibilities include exploratory analysis, multivariate testing, metric definition, data quality improvement, ETL pipeline development, self-service AI-enabled reporting, and translating statistical or predictive insights into product and business strategy. The role collaborates with Product, Engineering, Finance, and data teams to influence roadmap decisions and improve consumer engagement.

Leads CRM marketing analytics for Seller and Owner verticals by developing segmentation, targeting, personalization, customer journey, and campaign measurement strategies. Analyzes consumer behavior to improve engagement, retention, lead generation, cross-selling, and revenue. Builds statistical and machine learning models, integrates CRM data, establishes KPIs, communicates insights to stakeholders, and partners with Marketing, Data Engineering, and IT teams.