Top Data Science Jobs

Lead evaluation and improvement of the U.S. Census Bureau’s LLM Autocoder for survey write-in responses. Establish performance baselines, design reproducible experiments, analyze coding accuracy and errors, compare LLM and rule-based methods, assess expansion to additional survey fields, and guide engineers on model and preprocessing changes. Collaborate with government subject matter experts, interpret pilot and production results, and document recommendations and reusable technical practices.

Senior Data Scientist partnering with Product, Design, Engineering, Finance, and Marketing to drive user growth through data science, causal inference, experimentation, and analytics. Responsibilities include developing LTV and retention models, designing A/B tests, creating measurement frameworks and dashboards, translating complex analyses into recommendations, and strengthening data foundations for scalable experimentation.

Conduct hypothesis-driven analyses across claims portfolios, develop heuristic and predictive models, build scalable software tools, and communicate insights to technical and nontechnical stakeholders. The role collaborates with customer-facing, product, design, and sales teams; mentors junior data scientists; performs rigorous experiments; and continuously deploys maintainable, tested code to improve claims outcomes.

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.

Join a two-year Data Science Accelerator Program to rotate through analytical product development assignments. Assist with data cleaning, merging, feature creation, model validation, visualization, and client inquiries while learning statistical and machine learning techniques under senior data scientists' guidance.

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.

Develop and deploy predictive models, machine learning algorithms, and advanced analytics for Department of Defense missions. Responsibilities include data exploration, feature engineering, statistical analysis, model deployment and monitoring in secure environments, analytical visualization, stakeholder collaboration, and mentoring junior data scientists. The role requires an active TS/SCI clearance and experience with Python or R, AI/ML techniques, data governance, and federal compliance.

Analyze microbiome and longitudinal clinical datasets, develop microbiome metrics and biomarkers using statistics and machine learning, create visualizations and reports, draft clinical research documents, support product and study development, and contribute to scientific publications and proposals.

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.

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 role involves analyzing financial fraud data, developing methods for investigation, and presenting findings. Expected to manage projects over time.

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.

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.

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.

As a Data Scientist, you will shape data science efforts, work with teams to understand product usage, mentor junior staff, and build data products.

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 end-to-end data science projects to enhance Parafin's underwriting engine by developing predictive models, optimizing pricing, and collaborating with engineering teams.