Top Data & Analytics Jobs

Collects, processes, and analyzes data from multiple sources using R, Python, and SQL. Develops reports, visualizations, analytical methods, and data-driven insights while applying statistical and introductory machine learning techniques. Collaborates with internal and external stakeholders, documents project progress in JIRA, debugs code, clarifies requirements, and communicates findings through reports and presentations.

As a Senior Data Analyst, you will analyze complex data, mentor junior analysts, develop AI-based tools, and ensure data integrity while collaborating with cross-functional teams to drive insights and strategic decisions.

Leads analytics engineering and data modeling initiatives, building scalable transformation pipelines, dimensional models, semantic layers, and decision-ready datasets. Partners with business, data engineering, data science, and BI teams to translate operational needs into production-grade analytical products. Establishes governance, documentation, lineage, performance optimization, and modern development practices across enterprise, manufacturing, and supply chain analytics.

Analyze HR data to identify trends, opportunities, and actionable insights. Build Tableau or Power BI dashboards, develop workforce metrics, validate data, document governance processes, and communicate findings to technical and business stakeholders. The role supports data-driven HR strategies, process optimization, talent management, and organizational effectiveness while collaborating across HR and business teams.

Provides business intelligence and data analytics support for government customers. Extracts, cleans, analyzes, models, and visualizes enterprise data; gathers requirements; develops dashboards and reports; documents governance processes; improves workflows; and trains end users. Serves as a subject matter expert in Strategic Resource Management, manpower, resource planning, and risk-based program data. Supports government financial operations and may require travel and federal background eligibility.

Supports public health data extraction, management, cleaning, validation, harmonization, statistical and qualitative analysis, and evaluation. Develops analytic datasets and documentation, analyzes implementation and outcome measures, integrates mixed-methods data, and prepares technical memoranda, reports, tables, figures, and presentations. The role also uses Microsoft Office and CDC administrative systems while supporting government program monitoring and evaluation activities.

Maintains material master records, artwork, templates, and approvals in SAP and related repositories. Ensures master-data accuracy, compliance, and consistency; verifies records through reference documents and audits; documents procedures; supports internal and external stakeholders; escalates complex issues; and contributes to lean continuous-improvement initiatives. Performance is measured through data accuracy, responsiveness, and cost-saving improvements.

Manages master data, validates data quality, analyzes information from multiple sources, develops statistical models and reports, troubleshoots reporting databases, supports data integrity initiatives, and trains users on dashboards. The role also translates reporting requirements, recommends software solutions, and communicates findings to stakeholders.

Implements and supports software solutions, configuring platforms to client-specific data and business needs. Mines, cleans, maps, validates, and analyzes large datasets; communicates actionable insights; calibrates models; evaluates model performance statistically; and improves configuration support processes. The role also serves as a client-data subject matter expert, advises on data initiatives, and supports multiple concurrent projects.

Develops scalable analytics products using Python, Snowflake SQL, Power BI, Streamlit, and related tools. Integrates ERP and MRP data, builds dashboards and cloud-native applications, maintains Snowflake environments, and automates deployments through GitHub workflows and CI/CD. Partners with manufacturing, supply chain, and cross-functional teams to translate business needs into technical solutions, improve operational decision-making, and demonstrate measurable business value.

The Data Analyst will gather data from internal and external sources, create reports for teams and clients, analyze datasets using statistical techniques, identify patterns, and communicate insights. The role also requires staying current with data analysis and business intelligence trends, managing multiple projects, and supporting analytics initiatives for healthcare and pharmaceutical marketing clients.

Manage client-facing reports, data quality, reporting requests, and forecast models. Analyze business requirements and data to develop technical specifications, verify report accuracy, identify bottlenecks, and support immigration case teams, attorneys, paralegals, and clients. Maintain data quality scorecards, process guides, and reporting workflows while ensuring timely delivery and adherence to client standards and SLAs.

Perform forensic data analysis and fraud detection using SQL, Python/R, ML, big-data tools and visualization. Develop detection models/rules, evaluate anti-fraud tools, manage engagements, communicate findings to stakeholders, and lead project teams in investigations and compliance remediation.

The Big Data Analyst will evaluate datasets, improve analytical methods, support software developers, and assist end-users to enhance decision-making processes.

Develops advanced analytics using public and private healthcare data, integrates large longitudinal and claims datasets, creates research-ready datasets, translates research questions into analytic plans, documents data procedures and code, and drafts technical report methodology sections.

Own data quality, governance, KPI definitions, and reporting integrity for Verizon Value. Build and maintain Power BI dashboards, datasets, semantic models, scorecards, and automated reporting solutions. Investigate discrepancies, establish validation processes, standardize reporting, and collaborate with analytics, engineering, operations, client services, and Verizon stakeholders to improve data trust, reporting efficiency, and client outcomes.

Owns data quality, KPI governance, reporting accuracy, and business intelligence solutions for Verizon Value. Responsibilities include developing Power BI dashboards and semantic models, validating and reconciling data, investigating discrepancies, documenting reporting standards, automating reporting processes, and partnering with analytics, engineering, operations, client services, and Verizon stakeholders to improve data trust and reporting efficiency.

Analyzes, validates, reconciles, and extracts healthcare data from disparate systems using Excel and SQL. Supports SaaS implementation projects, customer troubleshooting, reporting automation through SFTP, and communication of findings to technical and nontechnical stakeholders. The role also assists with data integrity, issue resolution, customer updates, and implementation progress tracking.

Analyzes servicing, collections, application funnel, and contact-center data to identify performance gaps and inform business decisions. Builds automated reports, partner data files, Snowflake and dbt models, and operations dashboards. Maintains metric definitions, audits models, reconciles partner data, and develops business-case analyses. Uses AI tools to improve analytics workflows and collaborates with data engineering, product, and business teams.

Analyzes data and builds analytical datasets, data models, SQL queries, Python notebooks, dashboards, and reports using Databricks and BI tools. Identifies trends, validates data quality, translates business requirements into reporting solutions, documents data logic, and communicates insights to technical and non-technical stakeholders. The role also supports governance, security, lineage, and compliance across collaborative client delivery projects.

Analyzes structured and unstructured data to identify insights, develop algorithms, create dashboards and visualizations, apply statistical and machine learning methods, integrate data systems, and advise clients on data-driven decisions. Requires R, SQL, data analytics, visualization, machine learning, a bachelor’s degree, and TS/SCI clearance with polygraph. Python, data governance, and project management are preferred.

Analyzes and validates data to create dashboards, reports, notebooks, visualizations, and reusable analytical workflows. Partners with business, technical, and customer stakeholders to define questions, improve datasets, communicate insights, and support operational and revenue decisions. Uses SQL, Databricks, Python, cloud platforms, version control, and automation practices. Maintains data quality, documents assumptions, manages multiple analytical projects, and travels occasionally to lottery and corporate locations.

Paid data analyst intern to collect, clean, and analyze e-commerce and marketing datasets, build dashboards, generate customer and performance insights, support market research, and collaborate with marketing, product, and sales teams to drive data-informed decisions.

Analyze product telemetry, user signals, performance, behavior, feature adoption, and product metrics. Develop recurring reports, dashboards, and visualizations, investigate issues and trends, and provide insights supporting product initiatives and rapid iteration. Collaborate with Product Managers, Applied Scientists, Engineers, and stakeholders across China and the United States.

Designs enterprise data architectures and models while establishing governance, ownership, stewardship, metadata, and lineage practices. Facilitates stakeholder workshops, gathers requirements, documents business processes and solution designs, and partners with technical delivery teams. Supports data products, analytics, and digital transformation initiatives across manufacturing, supply chain, industrial IoT, and other operational environments. The role also contributes to scalable data platforms and operational and analytical use cases.