Top Data Science Jobs

Leads data science initiatives using machine learning, statistical modeling, and large-scale data analysis. Partners with software engineers and product managers to develop customer-focused products, builds and validates models across the full development lifecycle, translates technical findings into business outcomes, evaluates emerging technologies, and develops data science talent. Requires substantial experience with programming, machine learning, relational databases, cloud computing, and people management.

Develop Generative AI solutions for financial services using Python, PyTorch, LangChain, AWS, Spark, vector databases, multi-agent systems, and advanced RAG pipelines. Build, fine-tune, evaluate, validate, and deploy machine learning models across large numeric and textual datasets. Collaborate with data scientists, machine learning engineers, and product managers while translating technical findings into business outcomes.

Leads data science and machine learning initiatives for payment-network applications, including fraud, risk, merchant intelligence, and monitoring. Partners with data scientists, engineers, and product managers to build scalable models and AI tools. Responsibilities span model design, training, evaluation, validation, and implementation using Python, AWS, H2O, Spark, and other technologies. The role also requires stakeholder communication, innovation, and team talent development.

Build and operate supply chain data pipelines, models, integrations, quality controls, and dashboards supporting procurement, inventory, logistics, suppliers, and project analytics. Partner with analysts and business teams to enable forecasting, planning, scorecards, KPI tracking, and data governance. Contribute to cloud data architecture, engineering standards, tooling implementations, and productionizing analytics models across AI infrastructure and capital-intensive supply chain operations.

Build and deploy machine learning models for Waymo’s marketplace, including conversion, wait-time, retention, demand forecasting, pricing, matching, and vehicle positioning models. Apply reinforcement learning, design and evaluate experiments, collaborate with Engineering and Product, and present data-driven recommendations to leadership.

Develops advanced analytics, machine-learning, and AI solutions for quality monitoring, risk identification, root-cause analysis, and performance improvement. Builds and deploys models, dashboards, datasets, and automated workflows using statistical, predictive, NLP, and generative AI methods. Partners with technical and business stakeholders, communicates insights and recommendations, monitors solution value, and provides technical guidance. The role supports product, manufacturing, warranty, safety, and customer quality decisions in a regulated, office-based environment.

Build and evaluate fraud models for onboarding, login, account changes, and money movement. Develop labels, features, sampling strategies, thresholds, and production monitoring to detect account takeover, scams, money mules, and identity fraud. Transition third-party risk models to in-house solutions, measure model performance and drift, collaborate with fraud, risk, operations, and compliance teams, and evaluate AI agent workflows for transaction review and fraud-ring analysis.

Lead product analytics and data science for a member platform, shaping product strategy through behavioral analysis, experimentation, segmentation, retention and churn modeling. Own product metrics end to end, build trusted datasets using Fivetran, dbt and BigQuery, and implement testing, monitoring, lineage and documentation. Partner cross-functionally with product, engineering, finance, operations and go-to-market teams to identify growth opportunities and support roadmap decisions.

Develop and maintain human capital data strategies, analytics, dashboards, and data science tools for military and civilian workforce management. Apply predictive analytics, machine learning, and AI to identify trends, support recruitment and retention, improve professional development, and deliver decision products. Build analysis-ready data foundations, analyze secure and non-classified defense network data, improve existing tools, and collaborate with leadership and subject matter experts. The role requires Palantir Foundry experience, U.S. citizenship, and the ability to obtain a DoD Secret clearance.

Develops data science solutions for complex structured and unstructured datasets. Responsibilities include data exploration, cleaning, analysis, visualization, predictive modeling, algorithm development, quantitative analysis, and applying machine learning, AI, NLP, and text-mining techniques. The role partners with clients to transform disparate data into objective insights and decision-support tools, potentially supporting public-sector and classified environments.

Develops predictive models, algorithms, quantitative analyses, and visualizations from structured and unstructured data. Provides data science insights for resource management and workforce decisions, applies machine learning and natural language processing techniques, and leads complex solution development. Works with clients and teammates to transform disparate data into actionable information for informed decision-making.

Develop and strengthen client data science capabilities by analyzing complex structured and unstructured datasets, applying statistics and machine learning, evaluating AI/ML models, and translating findings into actionable insights. Collaborate with clients, mentor teammates, support defense and intelligence customers, and contribute to GEOINT, LLM, and all-source analysis efforts.

Analyze operational, financial, HR, and job-management data; build dashboards, predictive models, and business forecasts; identify and implement AI and automation opportunities; integrate AI tools through APIs and automation platforms; measure productivity and KPI improvements; support tool adoption and training; and ensure responsible data and AI practices.

Performs data preparation, cleansing, transformation, exploratory analysis, and predictive modeling. Develops analytical workflows, reports, dashboards, visualizations, forecasting solutions, and model validation processes. Collaborates with project teams to answer business and operational questions through data analysis, while documenting methodologies, assumptions, and outputs. Requires an active Secret clearance, bachelor’s degree, and at least three years of relevant experience.

Performs data preparation, exploratory analysis, predictive modeling, forecasting, visualization, and analytical model validation. The role supports machine learning workflows, creates reports and dashboards, documents methodologies, and collaborates with project teams to address operational and business questions. The position requires an active Secret clearance, a bachelor’s degree, and at least three years of relevant experience, with preferred experience in data platforms, automation, visualization, and government or logistics operations.

Develop algorithms, evaluate AI and machine learning models, and analyze complex structured and unstructured datasets to provide objective insights for clients. Collaborate with teams and stakeholders to understand business and intelligence questions, transform disparate data into actionable information, and support data analytics, visualization, AI governance, and intelligence-related initiatives. The role requires an active TS/SCI clearance and supports public-sector and national-security clients.

Leads a multidisciplinary team of data scientists and software engineers delivering production AI/ML and engineering intelligence platforms. Responsibilities include team development, technical architecture, engineering standards, governance, quality, security, operational readiness, cloud and platform direction, hiring, and cross-functional coordination. The role remains hands-on in architecture, reviews, critical problem solving, and delivery while managing distributed international collaboration.

Develop advanced statistical and machine learning models for national security missions. Analyze structured and unstructured data, engineer processing workflows, integrate authoritative sources, create dashboards, and deliver decision-support products. The role supports cloud-based analytical environments, data architecture, governance, operational assessments, and mission planning. Responsibilities include translating stakeholder needs into analytical solutions, documenting methodologies, presenting findings, and improving data quality across mission systems.

Develops data science solutions for aerospace mission challenges by analyzing complex structured and unstructured datasets, building predictive analytics, applying machine learning, optimizing algorithms, automating processes, and creating scripts. Works with customers and cross-functional teams to translate data into actionable insights for military leadership. Requires programming, statistics, machine learning knowledge, a bachelor's degree, and Secret clearance.

Leads the design, development, testing, and evaluation of AI and machine learning solutions. Directs data analysis, modeling, infrastructure, monitoring, and integration efforts while establishing standards for AI robustness, bias, explainability, failure modes, and technical controls. Manages large projects, advises clients, coaches teams, and develops reusable evaluation tools and evidence workflows for responsible AI deployment.

Develop and operationalize statistical, mathematical, geospatial, and data science models supporting CBP risk management and data-driven operational decisions. Responsibilities include exploratory data analysis, regression modeling, suitability modeling, GIS analysis, and scripting with Python, SQL, and R. The role requires independent analytical work, ArcGIS experience, and the ability to obtain TS/SCI clearance and DHS suitability.

Designs, builds, evaluates, and deploys machine learning, LLM, and agentic AI capabilities for cybersecurity detection, investigation, and response. Analyzes complex security data, develops models and evaluation frameworks, creates RAG and retrieval workflows, and partners with engineering teams to productionize and monitor AI systems. The role requires addressing adversarial, noisy data and balancing accuracy, explainability, latency, reliability, and operational impact.

Develop and maintain credit risk, underwriting, fraud, collections, and behavioral scoring models. Engineer features from financial, banking, healthcare claims, and alternative data. Own models from prototyping through production, ensuring interpretability, regulatory compliance, monitoring, validation, and recalibration. Collaborate with Data Engineering, Product, Risk, Compliance, and Finance teams to integrate model outputs and communicate insights.

Lead applied AI and data science work for recommendation and personalization systems. Partner with data scientists, engineers, and product managers to deliver customer-facing products; develop, train, evaluate, validate, and implement machine learning models; analyze large-scale numeric and textual datasets; apply statistical modeling, deep learning, causal inference, reinforcement learning, and recommender-system techniques; and communicate technical findings to business stakeholders while developing team talent.

Develop algorithms, systems, and analytical solutions that transform structured and unstructured data into actionable insights. Collaborate with clients and teams, evaluate AI and machine learning models, analyze complex datasets, and communicate findings that support informed decisions across government and private-sector challenges. The role may involve intelligence clients, AI governance, data visualization, and DoD analytical standards.