Top Data & Analytics Jobs

Maintains Workday item master data and integrated system records supporting procurement, clinical, charging, and financial workflows. Responsibilities include product onboarding, naming and spend categorization, charge and chart configuration, packaging and unit-of-measure maintenance, integration monitoring, issue resolution, documentation, and audit readiness. The role collaborates with Supply Chain, Finance, Revenue Integrity, Clinical, IT, and vendors to resolve data quality and integration issues within established governance standards.

Own marketing funnel analytics from end to end by monitoring metrics, diagnosing performance drivers with SQL and Python, building Snowflake/dbt models, and maintaining Periscope dashboards. Translate findings into actionable recommendations for leadership, partner with Marketing, Risk, and Engineering on strategy and release impact analysis, and use AI tools while validating their output. Support team development through knowledge sharing, code review, and mentoring junior analysts.

Analyze complex data to support business strategies, build data solutions and self-service tools, develop dashboards and metrics, and maintain data quality, governance, metadata, lineage, and access controls. The role partners with business and technology teams while using Python, R, Spark, SQL, Snowflake, AWS, and business intelligence tools.

Analyzes complex data to support business strategies, develops business intelligence tools, dashboards, metrics, and self-service data solutions, and manages data quality, metadata, lineage, definitions, security, and access governance. The role uses Python, R, Spark, SQL, AWS, and data visualization technologies while partnering with business and technical teams to deliver insights and monitor data quality.

Analyze complex data to support business strategy, build self-service data solutions, develop dashboards and metrics, and manage data quality, metadata, lineage, security, and governance. The role requires collaboration with business and technology teams, use of Python, R, Spark, SQL, and AWS, and delivery of data-driven insights within financial services.

Owns enterprise AI business intelligence and analytics, integrating data from cybersecurity, CMDB, ServiceNow, training, and AI platforms. Builds executive dashboards, portfolio health views, showback reporting, forecasts AI spending, automates data pipelines, applies A/B testing, and presents insights to senior leadership. The role also defines data models, reporting requirements, and dynamic row-level security for enterprise AI governance and adoption.

Analyzes complex data to solve business problems, develops self-service data solutions, dashboards, metrics, and visualization tools, and provides strategic insights. Manages data quality, metadata, lineage, definitions, access governance, and monitoring. Partners with business and technology teams while using Python, R, Spark, SQL, Snowflake, AWS, and data governance tools. The role is hybrid and supports innovation, business intelligence, and data management initiatives.

Analyze complex data to deliver business intelligence, dashboards, metrics, and strategic insights. Build data solutions using Python, R, Spark, SQL, Snowflake, and cloud technologies. Manage data quality, metadata, lineage, definitions, access governance, and monitoring while partnering with business and technology teams.

Conduct quantitative and qualitative analysis supporting global go-to-market and field services teams. Analyze retention, churn, product adoption, forecasting, territory design, and performance data; build dashboards, reports, queries, and automated data pipelines using Python and SQL. Partner with systems, operations, sales, and executive stakeholders to ensure data quality, prioritize requests, operationalize insights, and drive revenue-impacting decisions.

Own product analytics for embedded business areas, leading experimentation, root-cause analysis, business-case development, KPI reporting, and strategic recommendations. Build dashboards and Looker explores, partner with engineering teams to improve data models and reliability, present insights to leadership, use AI tools to improve analytics efficiency, and mentor analysts. The role requires advanced SQL, Python, statistical experimentation expertise, and experience with consumer fintech or similar B2C data.

Paid, full-time 11-week data analytics internship focused on fraud-ring identification, graph analytics, data extraction and cleaning, data engineering, visualization, customer-readable reporting, and communicating insights. The intern will use tools such as Tableau, Power BI, and Excel, make data-driven recommendations, and collaborate with cross-functional teams while participating in professional development and networking activities.

Collects, validates, analyzes, and maintains Reliability and Maintainability data for naval aviation systems. Reviews and scores Maintenance Action Forms, resolves documentation issues, attends flight debriefings, identifies maintenance trends and recurring issues, responds to data calls, and evaluates component repair production effectiveness using naval aviation maintenance reporting systems.

Builds dashboards and advanced analytics to monitor global Operational Excellence performance. Analyzes safety, quality, cost, delivery, and people metrics; standardizes KPI definitions; maintains data governance; identifies trends and improvement opportunities; supports business cases and scenario modeling; and prepares executive reporting. Partners with global site leadership to embed OpEx practices, align performance management, and translate strategy into measurable programs and outcomes.

The Data Analyst supports strategic planning and decision-making by analyzing academic, student, research, financial, human resources, and operational data. Responsibilities include developing dashboards and reports, identifying trends, validating data quality, preparing policy analyses and briefing papers, supporting accreditation and program reviews, and collaborating with leadership and business intelligence teams. The role also evaluates policies, documents analytical processes, and provides evidence-based insights for institutional initiatives.

Analyze mobile app activation, feature adoption, onboarding, engagement, retention, funnels, cohorts, and A/B tests. Build SQL and dbt models, dashboards, and self-service reports using BigQuery and GCP. Partner with product and engineering teams on instrumentation, identify data issues, automate reporting with AI tools, and communicate actionable insights to nontechnical stakeholders.

Analyzes and validates data from internal and external sources to support financial risk analytics and governance. The role monitors data quality, investigates exceptions, prepares reporting and presentations for risk committees and senior management, automates recurring processes, and supports liquidity, interest rate, capital, market, and regulatory risk analysis. It collaborates with Treasury, Balance Sheet Risk Management, data owners, and other risk partners while conducting ad hoc analyses and strategic initiatives.

Analyzes structured and unstructured datasets, identifies data quality issues, builds SQL database models and ETL processes, and creates Tableau visualizations. Translates technical findings into client-ready reports and presentations, supports financial and operational impact assessments, documents methodologies, and coordinates project activities with clients and internal teams.

Build reporting infrastructure from scratch by integrating data from McLeod, APIs, files, and spreadsheets; write optimized SQL; create KPI dashboards and reports in Power BI and Excel; automate recurring analysis using Claude and connected Microsoft tools; validate outputs against source data and the general ledger; and support budgeting, forecasting, cash flow projections, pricing, and strategic decisions.

Data Analyst Intern supporting Dow Jones data management projects through reporting, dashboard development, quantitative analysis, data exploration, and stakeholder communication. Responsibilities include delivering customer-facing reports, interpreting trends, building dashboards with visualization tools, and supporting data pipelines, models, algorithms, and visualizations. Candidates must be undergraduate students with quantitative coursework, SQL or Python knowledge, strong Excel skills, and an analytical, curious mindset.

Owns end-to-end customer analytics workstreams, including KPI frameworks, multi-source dashboards, reporting, data governance, quality assurance, and insight delivery for government digital communications programs. Presents recommendations to stakeholders, mentors junior analysts, leads Agile ceremonies, documents analytics practices, resolves data issues, and evaluates AI-assisted analytics tools.

Supports IT Development and Data Engineering by querying, analyzing, and reporting on enterprise data. Builds and maintains dashboards and reports using SQL and BI tools, assists with data quality and documentation, and handles ad hoc stakeholder requests. The role provides exposure to data warehousing, ETL, and data governance while working under senior team members.

Develop dashboards, visualizations, statistical analyses, SQL reports, and business insights for clients and senior management. Responsibilities include data quality assessment, data collection and transformation processes, reporting, dashboard template development, statistical modeling using R or SPSS, client collaboration, documentation, and presentation of findings. The role requires at least three years of data analysis experience, strong communication skills, advanced Excel and presentation capabilities, and proficiency with analytics and visualization tools.

Create dashboards, standardize and automate reporting, analyze business performance, validate data quality, resolve reporting issues, and guide stakeholders in interpreting results. Support Business, Finance, and Operations with management, forecasting, and transformation initiatives while promoting data-driven decision-making. The role requires strong stakeholder and change-management skills, data visualization and data management knowledge, fluent English and French, and three to five years of relevant experience.

Supports soccer analytics through data aggregation, processing, event and tracking data analysis, opposition analysis, and pre- and post-game reports. Produces concise visual reports and assists with ongoing projects and ad hoc requests from coaches and department leaders. The internship averages 15 hours weekly during the 2027 MLS Sprint Season, with possible continued employment.

Leads analytics for rapidly prototyped mobile games, designing experiments, building Looker dashboards, improving data quality, and guiding product and marketing decisions. Establishes analytical standards, governs AI-assisted analysis, enhances semantic layers and reusable AI skills, and partners with engineering on scalable data infrastructure. The role requires strong judgment in ambiguous, fast-changing environments and influence with senior stakeholders.