Top Data Science Jobs

Senior Data Scientist will design, validate, and deploy scalable ML models (recommendation systems, NLP), source and ensure data quality, assess model performance, produce visualizations, collaborate with stakeholders, and mentor junior team members to deliver data-driven solutions that optimize business outcomes.

Analyzes structured, unstructured, and semi-structured datasets using data engineering, machine learning, statistical analysis, visualization, and text-processing techniques. The role develops recommendations for data acquisition and enterprise data strategy, identifies patterns and anomalies, researches emerging methodologies, and presents findings to senior government leadership. It also requires collaboration with contractor teams and use of project management and documentation tools.

Graduate-level summer internship developing data science and machine learning solutions for lending member experience. Responsibilities include sentiment analysis, NLP topic modeling, feature engineering, exploratory data analysis, dashboard development in Power BI, and analysis of structured and unstructured data. The intern will use Python and SQL, communicate findings to technical and business stakeholders, document methodologies, and support AI-enabled analytics projects.

Supports data science and machine-learning initiatives for deposit products by retrieving, analyzing, and modeling large datasets in Azure Databricks. Develops propensity models, performs feature engineering, uses AI tools, and analyzes member behavior. Packages findings into executive-level presentations for senior management. This is a 12-week, on-site summer internship for students pursuing a relevant undergraduate or graduate degree with graduation expected December 2027 or later.

Data Scientist Summer Associate interns develop descriptive, predictive, and prescriptive models for credit risk, lending strategy, pricing, underwriting, and portfolio monitoring. Responsibilities include analyzing large datasets with Python, R, Scala, Spark, and SQL; validating models; creating dashboards and visualizations; generating business insights; and automating processes. The 12-week program requires current enrollment in a quantitative degree program with graduation expected December 2027 or later.

Supports AI, machine learning, and data science initiatives for Real Estate Lending. Projects may include LLM and AI agent applications, predictive modeling for loan refinancing, and advanced analytics on member and loan data. The intern will develop and evaluate models, translate data into insights and recommendations, create visualizations, document and present findings, and collaborate with stakeholders while applying ethical AI 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.

Lead data science projects from ideation through enterprise impact, building scalable and well-tested solutions that improve healthcare outcomes. Apply probability, statistics, machine learning, SQL, and Python to develop data-driven products and insights. Partner with stakeholders, assess product performance, identify strategic improvements, mitigate risks, and mentor teammates while aligning initiatives with business objectives.

Lead development of customized AI solutions for manufacturing clients. Analyze manufacturing data, build predictive models and tools, identify product opportunities, collaborate with customers and internal teams, and present data-driven findings to technical and non-technical stakeholders.

Own Fora’s growth operating model for forecasting, scenario planning, goal-setting, and strategic investment decisions. Partner with Strategy & Operations, Finance, founders, and executives to analyze business trends, size opportunities, model pricing and initiative impacts, and guide resource allocation. Mentor data team peers while establishing best practices, tools, processes, and standards.

Lead product analytics and experimentation for Fora’s travel marketplace. Analyze product usage and advisor behavior, define data instrumentation, guide roadmap decisions, build predictive and personalized models, and establish experimentation best practices. Partner closely with Product, Engineering, and Design while mentoring data team peers and improving processes, tools, and standards.

Lead marketing measurement and growth analytics through incrementality experiments, attribution, media mix modeling, customer value and retention modeling, and production machine learning. Partner with acquisition, lifecycle, membership, and growth leaders to guide investment and strategy. Mentor data teammates and establish best practices, processes, tools, and standards.

Leads analytical and scientific strategy for Fetch’s Play and Rewarded Apps businesses. Develops predictive and machine learning models, experimentation frameworks, causal analyses, feature pipelines, and measurement systems using Python and SQL. Partners with Product, Marketing, Engineering, and business leaders to improve monetization, engagement, retention, personalization, and marketplace outcomes. Translates complex findings into strategic recommendations, mentors data scientists and analysts, and establishes analytical best practices.

Develop and maintain credit risk models for origination, behavioral risk, underwriting, and portfolio management across Latin America. Own the full modeling lifecycle, including feature engineering, validation, backtesting, monitoring, calibration, and implementation. Analyze large financial datasets using Python and SQL, monitor portfolio and model performance, address data quality and selection bias, and translate analytical findings into credit strategies. Collaborate with Risk, Data, Engineering, Finance, and Operations teams.

Analyze petabyte-scale ad and app datasets to build dashboards, monitoring, and scalable analytics pipelines. Conduct exploratory analyses, root-cause investigations, A/B test evaluation, and model performance checks. Partner with engineering, research, and business teams to define KPIs, detect anomalies, and translate insights into product and business recommendations.

Analyze structured and unstructured data to guide Viewer Product strategy, improve Roku’s Home screen and discovery experiences, and identify growth opportunities. Build dashboards, reports, data pipelines, analytical models, and visualizations; design A/B tests; perform exploratory and advanced analyses; and communicate recommendations to product, engineering, marketing, and leadership stakeholders.

Develop and deploy data science, AI, and machine learning solutions for Unison business functions, including aerospace operations, fleet management, supply chain, and finance. Translate internal customer requirements into analytics tools and working solutions using complex datasets, LLMs, computer vision, neural networks, and advanced statistics. Collaborate with stakeholders, communicate technical findings, and support operational improvement initiatives.

Develop algorithms, predictive models, quantitative analyses, and visualization solutions for large structured and unstructured datasets. Explore, clean, analyze, and mine data using statistical and programming techniques, including machine learning, artificial intelligence, and natural language processing. Collaborate with clients to transform complex data into actionable insights and support informed decision-making. The role requires a TS/SCI clearance and offers opportunities to work across public and private-sector challenges.

Analyze structured and unstructured data for U.S. Space Force stakeholders. Responsibilities include sourcing datasets, defining KPIs, developing analytical scripts and machine learning models, automating processes, building Tableau or Power BI dashboards, and communicating insights to senior government and military leaders. The role also involves applying generative AI tools and supporting data strategy and decision-making.

Analyze structured and unstructured data to identify insights, develop KPIs and monitoring metrics, automate processes, build Tableau or Power BI dashboards, and apply machine learning models in production. Collaborate with stakeholders and communicate analytical findings to senior government and military leaders supporting the U.S. Space Force.

Develop data science algorithms, analytical software, ETL pipelines, and machine learning solutions using Python or R and AWS. Analyze complex structured and unstructured datasets, integrate software tools, and deliver objective insights for client decision-making. The role requires statistical analysis, predictive modeling, version control, and a TS/SCI clearance with polygraph. Intelligence-community and DevOps experience are preferred.

Lead data science for growth monetization, including subscription conversion, churn, pricing, packaging, paywalls, offers, and revenue modeling. Design rigorous experiments, establish metrics and unit economics for new business lines, and serve as the data science lead for a product area. Partner cross-functionally with product, engineering, design, and data science teams to drive revenue growth and build scalable data foundations.

Analyze and exploit GEOINT and supplementary data using advanced data science methods within GIS frameworks to support intelligence production. Develop approaches for intelligence questions, build dynamic geospatial web applications, and collaborate with scientists, engineers, and analysts. The role requires ArcGIS expertise, strong analytical and communication skills, and an active Top Secret clearance with SCI eligibility.

The Lead Data Scientist will enhance analytics through predictive modeling and data engineering, focusing on quality, feature generation, and continuous learning.

Leads agency-wide data science, reporting, data governance, and operations analytics. Responsibilities include developing performance indicators, assessing data quality, conducting statistical and geospatial analyses, supporting policy and research initiatives, coordinating data sharing, providing data to public stakeholders, using SQL to analyze large datasets, and contributing to public-facing transparency tools.