Top Data Science Jobs

The Data Scientist 2 role involves expertise in AI/ML, proficiency in Python, and contributions to data processing, modeling, and analysis to derive meaningful insights from large datasets.

The Staff Data Scientist designs and implements data science models, collaborates with stakeholders, mentors junior scientists, and ensures data quality to meet business needs.

The Data Scientist III will enhance cybersecurity operations using data science and machine learning techniques, developing analytical models, and integrating data from various sources to improve threat detection and monitoring.

Lead advanced analytical initiatives to optimize pharmaceutical distribution processes using data science methodologies. Design predictive models, analyze data, and present strategic insights to senior leadership.

The Risk Data Scientist will develop adaptive decisioning models for risk assessment in financial transactions, focusing on fraud detection and compliance, while managing model governance and deployment in a regulated environment.

As a Data Scientist, you will analyze data, develop algorithms, and utilize IoT and machine learning to solve complex problems for clients.

As a Data Scientist, you will collaborate with scientists to develop algorithms and software solutions for data analysis and machine learning, while engaging in multidisciplinary teamwork to meet project objectives.

Lead development, maintenance, and monitoring of credit risk models and loss forecasts. Extract and analyze large datasets with Python/SQL, automate reporting and dashboards, perform EDA and stress/sensitivity analyses, document audit-ready model deliverables, support model governance/validation, and communicate insights to stakeholders to inform credit policy and decisioning.

Analyze consumer loan portfolios to monitor performance, forecast losses, and recommend credit policies. Build and apply predictive models, time-series analysis, and segmentation to support portfolio risk management, due diligence, and governance reporting. Present findings to stakeholders and support audits.

Collect, clean, and analyze large healthcare datasets; build, test, and deploy statistical and machine learning models; develop scalable data pipelines; create visualizations and dashboards; collaborate with cross-functional teams; document methods and stay current with data science best practices.

As a Data Scientist in Marketing, you will enhance AI-driven marketing strategies, collaborate with teams to develop metrics, analyze marketing data, and recommend improvements for user engagement.

Collect, integrate, and prepare data from multiple sources; design data models, predictive algorithms, and ML solutions; build dashboards and visualizations; ensure data quality and support analytics for FBI financial management, client delivery, and business development.

Support human performance initiatives by entering, cleaning, and preparing data, maintaining databases/spreadsheets, and assisting basic performance analyses. Collaborate with multidisciplinary practitioners to identify data collection opportunities and prepare reports/presentations conveying trends and readiness insights. Use government systems to manage and analyze HP data.

Support MARSOC G2 IDST by analyzing complex data, applying statistical and machine learning methods, building predictive models, evaluating data sources, monitoring model performance, and developing data-driven solutions. Work on-site at Camp Lejeune under Top Secret/SCI clearance, collaborating on Agile teams and Git-based workflows.

Own the full analytics lifecycle: define problems, extract data, build and deploy models, design experiments, and create Power BI dashboards. Track business metrics, apply statistics and AI/LLM tooling, partner with cross-functional teams, and present findings to stakeholders to inform decisions.

Own statistical methodology for mission engineering: design experiments for large-scale simulations, apply Bayesian and regression methods, build scalable Python data pipelines and surrogate models, quantify uncertainty and sensitivity, produce decision-quality visualizations and reports, mentor teams, and support DoD/DARPA/intelligence programs.

Perform analytics and research on bike share and shared micromobility programs, build predictive models, create dashboards (Power BI), prepare reports, monitor data quality and vendor compliance, document data procedures, maintain internal databases, and partner with leadership and operations to inform planning and policy.

Lead and scale enterprise data science capabilities for operations-focused use cases in pharma. Build and deploy production ML/AI and optimization solutions, design reusable ML platforms, engage stakeholders to translate problems into high-impact analytics, and mentor teams while driving adoption and lifecycle management of digital products.

Senior individual contributor who drives product analytics, experimentation, and applied modeling. Owns growth and performance analyses, designs experiments with robust statistical evaluation, builds repeatable reporting, and partners with Product, Engineering, Operations, Clinical, and Finance to translate data into actionable product and operational decisions.

Senior IC for GTM analytics who builds and owns GTM data models, pipelines, and a semantic layer; runs deep analyses on funnel, conversion, forecasting, quota, and retention; partners with product data and engineering to ensure consistent data and operationalized metrics for non-technical stakeholders.

Analyze large complex datasets, build predictive models and A/B tests, create visualizations and dashboards, collaborate with engineers and stakeholders to improve data quality and support data-driven decisions, and stay current on data science best practices.

Assist senior data scientists with data collection, preprocessing, cleaning, and basic statistical analysis. Support model development, perform basic visualizations, and document processes and findings while learning and applying data science techniques.

Support ARNG CFO analytics by preparing and facilitating PPBC-G forums, coordinating across staffs, designing and executing data analyses and ML models, and developing/enhancing websites, applications, and secure database access for program portfolio analytics and executive presentations.

Early-career data scientist role to analyze user and content data, build metrics, design recommendation strategies (recall, ranking, cold-start, diversity), run A/B tests, evaluate experiments, explore LLM/multimodal applications, and improve data pipelines and feature logging.

Develop ETL, analytics, dashboards, and predictive/optimization models to support fleet planning, procurement, lifecycle and residual value analysis. Clean and combine data, build repeatable workflows, communicate findings, and support cross-functional adoption and process improvements.