Top Data Science Jobs

Develop data science, machine learning, AI, statistical, and visualization solutions supporting government audit and investigative products. Build and optimize data pipelines, integrate diverse data sources, perform ETL and modeling, troubleshoot applications, and document technical designs. Collaborate with stakeholders, database administrators, and IT teams; provide technical guidance, training, and support. The role requires coding in SQL, Python, R, and JavaScript, cloud data platform experience, U.S. citizenship, and eligibility for Public Trust clearance.

Analyzes enterprise incident, problem, change, API performance, and latency trends using Splunk, cloud observability tools, statistical modeling, AI, and machine learning. Develops predictive models, prototypes, dashboards, and remediation strategies to identify anomalies, improve automation, and resolve systemic issues across enterprise platforms. Collaborates with application, infrastructure, and network teams while providing technical guidance to stakeholders.

Lead performance marketing data science initiatives focused on lead segmentation, bidding optimization, targeting, and marketing spend allocation. Develop and deploy production-ready machine learning systems, establish research and ML operations roadmaps, build monitoring frameworks, and identify high-impact opportunities. Partner with engineering, marketing, vendors, and executives while mentoring data scientists and machine learning engineers and promoting rigorous, maintainable, and reproducible practices.

Develop and deploy machine learning models for personalization, customer journey optimization, recommendation systems, behavioral segmentation, and digital marketing effectiveness. Partner with engineering, marketing, sales, UX, and IT teams to build scalable data products, conduct A/B tests, translate business needs into data science solutions, and communicate actionable insights. Apply statistical analysis, causal inference, and emerging AI techniques while following documentation and model version-control best practices.

Lead data science for Mozilla’s advertising business by identifying high-impact opportunities, owning complex analyses, developing measurement and experimentation frameworks, analyzing revenue and performance, and translating findings into recommendations for technical partners and executives. Partner across Product, Engineering, Sales, Finance, and leadership to support business decisions in a fast-moving environment while balancing analytical rigor, pragmatism, and user privacy.

Lead data science partnership for Mozilla’s advertising business, identifying high-impact opportunities and owning complex analytics end to end. Develop measurement frameworks, experimentation strategies, instrumentation, and reporting for advertising products. Analyze revenue and performance, evaluate trade-offs, and communicate clear recommendations and uncertainty to technical teams and senior executives.

Leads the design, evaluation, deployment, and monitoring of production AI systems across generative AI, agentic AI, computer vision, forecasting, and optimization. Establishes rigorous metrics for accuracy, uncertainty, bias, hallucinations, drift, explainability, and failure modes; conducts experiments and communicates business impact, risks, and trade-offs. Builds solutions using foundation models, RAG, agentic workflows, unstructured data, and MLOps practices.

Supports DHS national security and law enforcement missions through data science, analytics, automation, and actionable intelligence. Responsibilities include collecting and transforming datasets with Python, R, and SQL; developing Power BI dashboards; identifying trends and anomalies; optimizing processes; and presenting findings. The role requires collaboration with stakeholders, handling ad hoc requests, and supporting analytic development from opportunity assessment through delivery.

Develop and implement statistical, machine learning, predictive, and optimization models to solve business challenges. Design data-driven experiments, prepare and validate structured and unstructured data, create visualizations, and communicate findings to technical and non-technical stakeholders. The role also leads adoption of new data science techniques and supports continuous improvement of organizational practices.

Develop NLP and machine learning solutions using Python, SQL, deep learning frameworks, and language models. Responsibilities include preparing structured and unstructured data, building ETL pipelines, analyzing text, creating classification and topic-modeling models, producing visualizations and reports, and communicating findings. The role requires advanced statistical analysis, technical education, and subject matter expertise in NLP, along with a TS/SCI clearance with polygraph.

Lead Data Scientist supporting a Data Modeling Team through technical targeting analytics, large-scale structured and unstructured data analysis, parallel processing, data modeling, and mission-relevant reporting. The role requires ECL and HPCC expertise, programming in Python, C, or SQL, clustered computing experience, and a TS/SCI clearance with polygraph.

Owns product measurement and decision thresholds across Ascend’s financial operations platform. Responsibilities include defining accuracy, success, and exception metrics; auditing production scores; partnering with Product and Engineering on instrumentation; deploying models for confidence scoring, reconciliation, collections, and recovery; monitoring calibration, drift, and realized outcomes; designing experiments; and using product data to inform the roadmap.

Analyze marketing and business performance using SQL, statistics, econometric modeling, Bayesian regression, causal inference, and A/B testing. Build marketing measurement models, integrate customer and event data, develop reporting infrastructure and dashboards, evaluate marketing spend, and provide actionable recommendations to optimize growth. Partner with Marketing, Product, Engineering, Finance, and executives across multiple brands.

Develops predictive and deep learning models for engineering and physical systems, including data preprocessing, probabilistic modeling, optimization, and scalable production data pipelines. Collaborates with simulation engineers and customers to integrate AI models into simulations, support product development, and deliver practical solutions. The role includes customer presentations, onboarding, on-site collaboration, and travel to international customer sites.

Supports GEOINT mission operations through data exploitation, analytical methodology development, and structured and unstructured data analysis. Uses Python and SQL to manipulate, analyze, and visualize data, collaborates with technical teams on scalable solutions, and contributes to emerging intelligence capabilities. The role is onsite in Springfield, Virginia, and requires an active TS/SCI clearance with willingness to undergo a CI polygraph.

Conducts statistical analysis, data mining, predictive modeling, data visualization, and AI/ML development using large intelligence datasets. Builds automated data ingestion and analytics workflows, improves data quality and architecture, and supports intelligence planning and operational decision-making. Collaborates with analysts, engineers, and mission partners to develop tools, models, and capabilities that enhance situational awareness and intelligence operations.

Develops predictive models, quantitative analyses, data visualizations, and machine learning solutions for Department of Defense clients. Responsibilities include data exploration, cleaning, mining, statistical programming, natural language processing, text mining, dashboard development, and advising stakeholders on actionable insights. Requires experience with Maven Smart System and a TS/SCI clearance.

Develop machine learning and advanced analytics models for sparse, noisy, and adversarial intelligence datasets. Translate analytic questions into technical requirements, assess data quality, recommend technical approaches, communicate findings to technical and non-technical stakeholders, and support automated analytics workflows for national security missions.

Analyzes internal and external marketing, sales, customer, and product data to develop predictive models, forecasts, dashboards, and actionable business insights. Builds data pipelines and BigQuery queries, performs data preparation and experimentation, and communicates findings through visualization tools. Guides generative AI adoption, develops AI agents and workflow automations, supports data governance, and partners with cross-functional teams to improve decision-making and marketing operations.

Develop predictive analytics, machine learning models, AI services, and enterprise data science capabilities. Prepare and analyze complex datasets, implement LLM-based solutions, fine-tune and evaluate models, and collaborate with architects, cloud engineers, and product leaders on scalable analytics platforms. The role also supports architectural decisions, data-driven applications, dashboards, and sustainable development practices within a Department of State modernization program.

Develop machine learning, statistical, data mining, graph-based, and heuristic algorithms for national security applications. Build and optimize AI/ML and large language models, including information retrieval workflows. Analyze varied datasets, create feature vectors, design experiments, evaluate models using standard metrics, produce visualizations, and translate subject matter expertise into production analytics. Guide analytic development efforts and integrate prototype algorithms into analyst workflows.

Leads data science and advanced analytics supporting Intelligence Community mission execution and national security objectives. Applies Python, R, Ruby, process automation, and large-scale data analysis to produce intelligence and targeting products. Collaborates with technical, executive, and government stakeholders, participates in peer reviews, and supports novel analytic methodologies. Oversees project operations, schedules, budgets, status reporting, issue resolution, and productivity goals. May lead teams through hiring, onboarding, performance management, and professional development.

Leads data science efforts supporting national security and Intelligence Community missions. Applies analytics and automation to large datasets, develops intelligence and targeting products, participates in advanced analytic peer reviews, and collaborates with technical, executive, and government stakeholders. Oversees project operations, schedules, budgets, status reporting, issue resolution, and productivity goals. May lead teams and support hiring, onboarding, and performance development.

Conduct workforce analytics and applied organizational research on attrition, mobility, engagement, performance, and planning. Analyze and validate HR data using SQL, R, or Python; apply statistical testing and regression; translate business questions into actionable insights; and communicate findings through visualizations, reports, and presentations. Partner with HR stakeholders while maintaining the accuracy, documentation, confidentiality, and integrity of sensitive workforce data.

Develops machine learning, statistical, data mining, graph-based, and large language models for national security applications. Analyzes datasets, creates feature vectors, prototypes and validates algorithms, builds experiments, generates visualizations, and implements analytics in production frameworks. The role collaborates with subject matter experts, optimizes GPU-based model training, supports LLM and RAG solutions, and guides analytic development efforts. An active TS/SCI clearance with polygraph is required.