Top Data & Analytics Jobs

Analyze large-scale Human Capital and workforce datasets, develop predictive models, automate data workflows, and build executive HR dashboards using SQL, scripting languages, Tableau, or Power BI. Integrate and validate data from multiple systems, apply AI/ML capabilities, and communicate actionable findings to senior leaders and nontechnical stakeholders. The role requires an active TS/SCI clearance and supports federal workforce analytics and decision-making.

Designs and maintains scalable data pipelines and architectures for operational, intelligence, and mission data. Develops dashboards, visualizations, data models, and AI-enabled analytics using Python, Maven Smart System, Palantir, and Power BI. Performs data integration, cleansing, scraping, exploitation, and predictive analysis while supporting C-UAS operations, assessments, acquisition decisions, and strategic planning. Produces technical documentation and executive briefings, ensures data governance and security, and collaborates with mission stakeholders.

Review robot task videos and annotations for accuracy, provide feedback to annotation teams, refine quality guidelines, coach teleoperation pilots, monitor data and performance metrics, and improve operational processes. The role partners with Autonomy and Operations teams to support reliable, high-quality datasets for training and evaluating robotic systems.

Conducts data collection, cleaning, management, statistical and computational analysis for education policy research. Responsibilities include building reproducible ETL pipelines, creating visualizations and research materials, applying machine learning and natural language processing, validating model outputs, managing restricted-use data, reviewing analyses, and coordinating with external collaborators. Senior responsibilities include overseeing analytical projects, documenting methodologies, managing compute and API costs, and serving as a technical contact.

Analyze consumer demographics, shopping behavior, marketing performance, order structures, demand forecasts, and customer satisfaction data. Develop forecasting models using time series, machine learning, clustering, XGBoost, and regression. Design surveys and ROI methodologies, evaluate marketing campaigns, produce weekly operational and forecasting reports, and present findings to management while supporting marketing operations.

Analyzes consumer demographics, purchasing behavior, marketing performance, industry trends, order structures, and SKU-level data. Develops demand forecasts using SARIMA, machine learning, clustering, XGBoost, regression, and time-series methods. Designs surveys, evaluates campaigns and ROI, measures customer retention, prepares operational and marketing reports, and presents findings to management. Supports marketing operations and recommendation-system improvements.

Develop and test mathematical models for sports betting pricing and risk management. Collect, clean, and analyze sports and betting datasets to identify trends and inform trading strategies. Build quantitative models and automate analytical processes using programming languages such as Python or C#. Collaborate with senior analysts, traders, engineers, and product managers, document methodologies, and communicate findings while continuing to develop expertise in quantitative analysis and betting markets.

Develop and maintain data pipelines, scalable data models, analytics datasets, and Power BI reporting solutions for renewable energy construction and preconstruction operations. Integrate cost, labor, project, scheduling, and operational data to support benchmarking, forecasting, estimate accuracy, and predictive analytics. Collaborate with estimators, engineers, procurement, project controls, operations, and leadership while using Databricks, Python, SQL, GitHub, and AI-enabled development practices.

Leads the enterprise data management strategy, Data Operations organization, data governance, stewardship, quality, taxonomies, metadata, and master/reference data programs. Partners with engineering, product, business, regulatory, and audit stakeholders to improve data architecture, lineage, controls, lifecycle management, and commercialization of proprietary data assets. Oversees third-party data providers, automation initiatives, operating metrics, change governance, and organizational growth while preparing data for AI, machine learning, semantic search, and advanced analytics.

Analyze product, user, transactional, and repayment data to develop risk and underwriting models, reduce losses and fraud, monitor model performance, and guide product and growth strategy. Build Looker dashboards and LookML models, conduct segmentation and experimentation, measure CAC and LTV, and communicate actionable insights to product, engineering, marketing, finance, and leadership.

Leads qualitative and quantitative market research programs from proposal through presentation, combining survey design, statistical analysis, qualitative synthesis, AI-enabled analytics, and dashboard development. Manages client relationships, identifies business opportunities, presents strategic insights, and supports account growth. Collaborates with public relations, marketing, creative, and strategy teams while overseeing research staff and projects.

Leads the strategy, architecture, and development of scalable data engineering, analytics, cloud, and AI platforms. Oversees Snowflake data warehouses, AWS infrastructure, SQL and Python pipelines, orchestration, data quality, observability, governance, and reliability. Builds data foundations for machine learning, generative AI, embeddings, vector search, and RAG applications. Provides technical leadership, mentors engineers, partners with executives and cross-functional teams, and drives AI transformation, platform modernization, and engineering standards.

Leads the strategy, architecture, development, and operation of scalable data and AI platforms. Oversees data pipelines, Snowflake architecture, AWS infrastructure, data quality, observability, governance, and analytics enablement. Guides machine learning and generative AI data foundations, including embeddings, vector search, RAG, model pipelines, and evaluation. Mentors engineers, establishes technical standards, manages cross-functional initiatives, and partners with executives and business stakeholders on AI and data priorities.

Leads data science and knowledge management efforts by tracking research questions, governing metadata, improving data discoverability, developing tagging and classification schemes, and integrating research products into dashboards. Uses Databricks Unity Catalog, OpenLineage, and ESRI metadata APIs while applying Department of War and Intelligence Community tradecraft standards. Requires TS/SCI clearance and supports classified client environments.

Researches and develops equity execution models, transaction cost models, order-routing strategies, and analytical tools. Applies statistical, mathematical, computational, and machine learning techniques to forecasting, sentiment analysis, execution optimization, performance measurement, and risk attribution. Collaborates with electronic trading, development, technology, and model validation teams to assess, document, maintain, and deploy commercially viable trading algorithms.

The Staff Data Reliability Engineer ensures data integrity, quality, freshness, and availability across enterprise pipelines. Responsibilities include defining data SLOs, implementing observability, building resilient Informatica and Python/PySpark pipelines, automating validation and recovery, eliminating operational toil, leading data incidents and postmortems, creating runbooks, and applying AIOps, machine learning, and DataOps practices to detect anomalies and self-heal data workflows.

Develop and maintain SQL-based data views, ETL workflows, and cloud data warehouse processes supporting CMS healthcare research data. Ingest new data sources, optimize database performance, document business logic, support production data loads, and collaborate with analysts, technical leads, and CMS partners. The role also involves data quality, monitoring, permissions, recovery, troubleshooting, and occasional off-hours or weekend production support.

Analyzes operational performance and financial-impact data for Philadelphia’s Water Department. Responsibilities include acquiring and cleaning large datasets, building data models and views, applying statistical and machine learning methods, identifying patterns, automating predictive and prescriptive analytics, and communicating insights to stakeholders. The role supports resource allocation, asset management, leak detection, water-loss mitigation, and revenue integrity. It requires onsite work, Philadelphia residency, off-hours availability, and participation in an on-call rotation.

Supports the enterprise data and analytics platform by building Microsoft Fabric lakehouses, warehouses, pipelines, semantic models, and Power BI reporting. Integrates D365, manufacturing, warehouse, supply-chain, IoT, and operational data; develops SQL and DAX solutions; implements data quality, governance, security, monitoring, and documentation; and troubleshoots production issues. The role also supports AI-enabled analytics and collaborates with business teams, vendors, and technical stakeholders in a manufacturing environment.

Manage data analysis for transaction monitoring, risk identification, and compliance. Analyze high-volume transaction data using SQL, Python, Splunk, and visualization tools; conduct root-cause investigations; design risk data architectures; identify process and reporting improvements; advise business and product teams; and translate technical findings into executive recommendations. The role also involves stakeholder liaison, regulatory alignment, data integrity, and managing concurrent analytical projects.

Supports data extraction, cleaning, analysis, visualization, ETL pipeline development, automated scripting, and machine learning model evaluation. The intern collaborates with data scientists and cross-functional teams, develops analytical tools, delivers actionable insights, performs ad hoc analyses, and presents project accomplishments to leadership. The three-month spring internship is intended for a currently enrolled bachelor’s student fulfilling a graduation requirement.

Designs, develops, and maintains scalable data warehouses, data lakes, platforms, and ETL/ELT pipelines. Builds batch and streaming workflows, processes structured and unstructured data, optimizes cloud storage and pipeline performance, and implements data governance and lifecycle management. Guides multidisciplinary teams in agile environments while delivering mission-focused data engineering solutions.

Leads analytics strategy for Faire’s Discovery pillar, informing search, recommendations, ads, and marketplace decisions. Builds and manages a high-performing strategy and analytics team, establishes analytical rigor and experimentation standards, owns key metrics and datasets, and develops self-serve data tooling and operating systems. Partners cross-functionally to identify opportunities, improve decision-making, and scale analytics practices across the company.

Manage and support analytics initiatives, mentor analysts, prioritize business-critical projects, and develop scalable data processes. Conduct data modeling and analysis, maintain data quality, automate workflows, and translate complex findings into actionable recommendations. Partner with product managers, business leaders, clients, and executives to advance data-driven decision-making while supporting compliance, reporting standards, and stakeholder needs.

Supports data engineering, analytics, data governance, dashboard development, ETL, and reporting projects across business and IT teams. Interns may build Power BI dashboards, analyze data trends, improve data quality, develop analytics solutions using AI and machine learning tools, and document complex processes. The role requires collaboration with stakeholders, strong communication, and familiarity with Python, SQL, cloud platforms, ETL frameworks, and reporting technologies.