Top Data & Analytics Jobs

Leads enterprise marketing measurement and consumer analytics across media, product, and retail businesses. Develops marketing mix modeling, experimentation, attribution, and performance measurement strategies; identifies growth opportunities; translates complex data into executive-level recommendations; partners with Marketing, Finance, Consumer Insights, and Analytics teams; and advances AI-enabled analytics capabilities and organizational maturity.

Lead and develop a team of partnership analysts; translate business questions into analytical frameworks, experiments, forecasts, and ROI models. Build dashboards and reporting infrastructure, analyze cohorts, funnels, retention, and partner performance, and own measurement frameworks for growth initiatives. Partner with Business Development, Engineering, Product, and Marketing to shape partnership strategy and communicate data-driven insights to technical and non-technical leaders.

Supports Department of Defense infectious disease surveillance through data collection, standardization, management, analysis, visualization, and integration. The role implements DHIS2 across laboratory partners, automates data pipelines, develops Tableau dashboards and surveillance reports, establishes data requirements, trains clients, troubleshoots systems, and provides analytical and programmatic support to GEIS leaders and stakeholders.

Conducts data collection, cleaning, validation, statistical analysis, predictive modeling, forecasting, and visualization. Develops reports and recommendations, collaborates with cross-functional teams, supports data governance and process improvement, and contributes to strategic initiatives. The role also provides occasional guidance and training to junior analysts while maintaining data confidentiality, quality, privacy, and compliance.

Designs, builds, and maintains data pipelines, processing systems, APIs, ETL processes, and data integration infrastructure. Implements data quality and governance practices, supports data scientists and analysts, and works with data warehouses, data lakes, cloud technologies, and large datasets. The role also requires ongoing learning about data technologies and occasional driving.

Supports enterprise data architecture initiatives involving data sources, integrations, pipelines, cloud technologies, IoT and telematics data, governance, quality, visualization, artificial intelligence, and machine learning. The intern will document data flows, develop proof-of-concepts, create architecture diagrams and dashboards, analyze data for business insights, and collaborate with architects, engineers, analysts, and stakeholders to deliver a meaningful summer project.

Owns the design, development, optimization, and lifecycle management of Tableau dashboards, data products, and procurement reporting solutions. Analyzes spend, sourcing, supplier, contract, and accounts payable data; translates findings into recommendations; supports Tableau Server governance; and enables self-service analytics. Partners with procurement and cross-functional stakeholders, presents insights to senior leaders, and evaluates AI-enabled opportunities to improve business outcomes.

Supports Global Supply Chain teams by identifying data-driven improvement opportunities and developing dashboards, reports, data models, automation, and analytics solutions. The intern will cleanse, validate, visualize, and analyze data using Excel, Power BI, Python, and SQL; evaluate AI and machine learning outputs; map processes; research responsible AI practices; and present recommendations to leadership and business stakeholders.

Support analytical projects across Gartner's BTI and Product teams: analyze large datasets, build dashboards and reports, apply ML/AI and LLM tools, assist data pipeline setup, collaborate with data engineering and IT, and communicate insights to stakeholders. High-performing interns may receive full-time offers.

Lead and develop a team of Data Analysts while overseeing analytics projects, reporting, data governance, and self-service BI solutions. Partner with engineers, data scientists, and business leaders to establish trusted datasets, improve data quality, communicate metrics, and advance predictive analytics and AI-enabled decision support. Coach technical and non-technical staff in statistical methods and data literacy, evaluate modern analytics technologies including Microsoft Fabric, and drive insights that improve manufacturing performance, quality, and operational efficiency.

Support the design, development, and maintenance of data pipelines, workflows, and cloud-based data platforms. Build reliable data assets through ingestion, transformation, profiling, validation, monitoring, and data modeling. Collaborate with cross-functional teams to support analytics, reporting, automation, machine learning, and AI initiatives. Interns will gain experience with Python, SQL, ETL/ELT, Snowflake, cloud technologies, GitHub, and AI tools while receiving mentorship and professional development.

Data Engineer Interns support data pipelines, workflows, and platforms that enable analytics, reporting, automation, machine learning, and AI initiatives. Responsibilities include ingesting and transforming structured and unstructured data, applying data quality and validation practices, collaborating on scalable data solutions, and using Python, SQL, ETL processes, cloud technologies, and AI tools. The role includes mentorship, Agile exposure, and hands-on experience supporting data assets for insurance business needs.

Designs, develops, deploys, maintains, and optimizes ETL processes and cloud-based system integrations for healthcare data warehousing and business intelligence. Works with DHA and Cerner inpatient and outpatient data, develops database procedures, validates migrations, performs data mapping and modeling, and supports data science and machine learning teams. The role also documents processes, tunes performance, captures client requirements, and manages data transformation initiatives.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

As a Machine Learning Engineer, you will enhance internal libraries for deep learning, collaborate with researchers, and optimize workflows for cost savings.

Lead the development of enterprise data engineering frameworks and platform capabilities for Orbit and Book of Work on Helix. Design and implement reusable pipelines, automation, AI-enabled workflows, data processing, APIs, metadata systems, observability, and platform integrations. Establish engineering and QA standards, guide architecture, write and review production code, support project planning, and own production reliability through incident response, root-cause analysis, and continuous improvement.

Leads enterprise performance and analytics strategy, including Business Intelligence, executive dashboards, KPI governance, reporting automation, data standards, and decision support. Partners with Finance, IT, and business leaders to improve forecasting, planning, operational performance, and value creation. Oversees Power BI and Microsoft Fabric initiatives, enterprise reporting architecture, mergers and acquisitions analytics, Board reporting, and self-service reporting. Supervises and develops analytics personnel while promoting enterprise-wide data-driven decision-making.

Leads advanced data analytics, statistical modeling, predictive analytics, and business intelligence for supply chain and logistics operations. Analyzes complex datasets, develops forecasting and optimization models, creates Tableau or Power BI dashboards, monitors KPIs, and translates findings into recommendations for government stakeholders. Provides technical leadership, quality oversight, and mentorship to junior analysts.

Develops and maintains insurance pricing and predictive models, analyzes premiums, losses, claims, and exposure data, evaluates profitability and emerging risks, supports rate filings and actuarial analyses, and delivers recommendations to leadership. The role also ensures data integrity, prepares financial reporting, automates workflows, and collaborates with product, actuarial, and business teams to improve pricing strategies and operational efficiency.

Designs, builds, and leads enterprise data and AI platforms across Azure and Databricks. Develops scalable batch and streaming pipelines with Azure Data Factory, Databricks, and Apache Spark; implements DevSecOps, CI/CD, infrastructure as code, security, governance, data quality, and metadata standards. Supports analytics, machine learning, and AI workloads while mentoring engineering teams and partnering with stakeholders on enterprise data outcomes.

Develop and maintain BI dashboards and ETL pipelines, transform and integrate structured and unstructured data, build analytical models and forecasts, apply machine learning and distributed computing (Databricks/Spark), create actionable visualizations (Qlik/Tableau/Power BI), and present insights to leadership while working in a cleared defense environment.

Lead licensing analytics for Disney Consumer Products, supporting Retail and Marketing through performance analysis, consumer insights, market trends, dashboards, and strategic recommendations. Translate business needs into data requirements, curate structured and unstructured data, build automated pipelines, develop self-service reporting, and improve data governance and architecture. Lead cross-functional analytics projects, communicate complex findings clearly, and guide technical transformation involving visualization, AI, and process automation.

Analyze and optimize e-commerce pricing strategies using sales, demand, customer behavior, competitive pricing, AI, and experimentation. Develop pricing models, measure elasticity, evaluate revenue and margin impacts, monitor competitor prices, and build dashboards, alerts, and scenario analyses. Translate analytical findings into recommendations and partner with Ecommerce, Marketing, Product, and Finance teams to improve profitable growth.

Leads advanced people analytics using Workday as the foundation for workforce insights, planning, retention, compensation, and talent decisions. Develops analytical datasets, metrics, dashboards, predictive models, and executive reporting; establishes data definitions, governance, quality controls, and architecture standards. Partners with HR Technology, Finance, HR leaders, and business executives to translate complex workforce data into strategic recommendations. Serves as a Workday and people-data subject-matter expert, mentors analysts, and influences enterprise decisions through clear storytelling.

Leads Magellan Health’s enterprise data and analytics strategy, modernization, engineering, governance, business intelligence, and AI/ML enablement. Oversees data platforms, pipelines, quality, lineage, compliance, and reporting while partnering with clinical, operational, and financial stakeholders. Builds and develops a 30+ person organization, manages a $3M–$5M budget, oversees vendors, and presents investment cases to executive leadership. Drives transformation from a low-maturity environment to a governed, insight-driven enterprise data platform.