Top Data Analyst Jobs

Support the design, development, testing, deployment, and production support of data analytics processes. Analyze data from multiple sources, develop SQL queries, ETL pipelines, dashboards, and visualizations using SAS and Power BI, and provide reporting and recommendations. Collaborate on Agile Scrum projects, resolve data and job issues, and deliver solutions under tight deadlines with minimal guidance.

Leads complex quantitative and qualitative analysis for Claims Leadership, producing forecasts, reports, dashboards, KPI frameworks, and actionable recommendations. Analyzes multiple data sources, identifies trends and root causes, supports strategic decisions, documents processes, and consults with cross-functional partners. Coaches peers on analytical methods and applies statistical research, visualization, and data storytelling techniques to improve business outcomes.

Analyzes large-scale payment datasets to identify optimization opportunities and deliver recommendations that support merchant growth. Builds scalable analytics solutions, ETL pipelines, automation, and self-service tools; leads A/B tests and complex data investigations; develops dashboards; and translates findings into actionable narratives for technical, commercial, and product stakeholders. The role also supports mentorship, knowledge sharing, and analytical best practices.

Analyze product and healthcare billing data to support product decisions, reporting, experimentation, and claims collection improvements. Build and maintain dashboards, develop scalable datasets, conduct A/B testing, create data visualizations, and communicate actionable insights. Collaborate with product stakeholders, data scientists, and engineers on data modeling, OKRs, data quality, and pipeline reliability for Billing and Payments features.

Supports private-market document processing, data-quality reconciliation, exception triage, workflow management, and offshore team coordination. Serves as a subject-matter expert on private-market data, analyzes trends, documents operational logic, identifies process improvements, and collaborates with Product, Data, and Engineering teams on roadmap and systemic fixes. Provides operational summaries and data-quality reports to support client-facing teams.

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 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.

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.

Leads enterprise compliance testing analytics, tooling strategy, and analytical projects. Partners with engineering, data science, legal, compliance, risk, and executive stakeholders to identify and mitigate compliance risks. Evaluates analytical tools, researches emerging practices, communicates findings through reports and presentations, and mentors junior staff. The role requires advanced data analysis, statistical or econometric modeling, large-scale data manipulation, data governance, and people management experience.

Paid, full-time data analyst internship supporting business planning and data operations. Responsibilities include documenting data definitions, business rules, and data quality requirements; integrating data from multiple sources; completing roadmap projects to improve process efficiency; and identifying data-driven strategies to enhance business performance. Interns also participate in professional development, networking, mentorship, community service, and final presentations.

Analyze reinsurance data and business processes, gather requirements, create data mappings and flow diagrams, and support FAIRR Data Hub solutions. The role validates data quality, governance, reconciliation, and technical specifications while partnering with business, technology, architecture, engineering, and governance teams. It also contributes to reporting, AI-enabled analytics, solution testing, stakeholder communication, and mentoring junior analysts.

Build Confido’s analytics layer by creating dashboards, reports, metrics, and analytical tools for internal and customer users. Analyze large financial and operational datasets with advanced SQL, identify trends and inefficiencies, and translate findings into actionable recommendations. Partner with product, engineering, customers, and other stakeholders to improve data models, deliver analytical projects, and support decision-making across retail, finance, and operations.

Owns fraud and market-abuse detection models, rules, and partner-facing surveillance reporting across trading data. Investigates wash trading, collusion, hedging, reverse trading, and other suspicious activity; calibrates thresholds, validates false positives, maintains data quality, and produces evidence-based findings. Requires strong SQL, cloud data warehouse experience, futures and derivatives knowledge, anomaly detection expertise, and the ability to communicate findings to partners and executives.

Lead product analytics for Enterprise Data products, validating analytical tools, assessing methodology risks, researching emerging practices, and translating complex data into actionable insights. Manage validation projects, communicate findings through reports and presentations, and coach junior staff. The role requires advanced data analysis, statistical or econometric modeling, predictive analytics, large-dataset analysis, data governance, and people leadership.

Analyze marketplace and product performance using SQL, support experiments and advertising-effectiveness studies, build reusable datasets, QA metrics, and document analytics. Collaborate with analytics engineers, data scientists, product managers, engineers, and commercial teams while developing skills in statistics, causal inference, Python/R, and marketing science.

Own analytics engineering and the data transformation layer by designing data models, warehouses, cubes, semantic layers, and governance frameworks. Improve data quality, observability, metadata, self-service analytics, dashboards, and reporting platforms. Analyze large datasets, optimize queries, conduct testing and code reviews, support modernization initiatives, and collaborate across teams to deliver trusted metrics and insights.

Analyze player behavior, product performance, revenue, retention, and engagement for Zynga Poker. Design experiments, dashboards, ETL pipelines, telemetry, fraud models, and business intelligence solutions. Partner with product, game design, economy, and consumer insights teams to guide decisions and improve player experiences. Contribute to AI-enabled analytics workflows, game integrity initiatives, and analytics best practices.

The Senior Data Analyst will lead metrics definition, reporting, statistical analysis, experimentation, dashboard management, and pricing analytics. The role involves building data pipelines, collaborating with data engineers on data assets and feature stores, investigating complex business questions, and translating analytical findings into strategic recommendations for product, pricing, and senior leadership. Strong SQL, statistics, econometrics, communication, and cross-functional collaboration skills are essential.

Drive AI automation for card data by developing data solutions, business intelligence tools, metrics, dashboards, and data-quality monitoring. Analyze complex structured and unstructured data, establish data governance and lineage, support access governance, and partner with technology and business teams. The role requires scripting, querying, visualization, AWS development, and experience applying LLM technologies to data strategies and process improvement.

Analyze complex data to support business strategy, build self-service data solutions, develop dashboards and metrics, and improve data governance and quality. The role partners with business and technology teams, manages data access and metadata, monitors data quality, and applies Python, R, Spark, SQL, AWS, and visualization tools across innovation, business intelligence, and data management initiatives.

Analyze complex data to solve business problems, build self-service data solutions, develop dashboards and metrics, and deliver strategic insights. Responsibilities also include data quality management, metadata and lineage governance, access controls, and collaboration with technology teams. The role requires scripting, data querying, business intelligence visualization, AWS development, and experience with structured and unstructured data.

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

Manages configuration and data lifecycle activities for flight-test documentation and records. Maintains configuration control records, reviews and validates test evaluation worksheets, archives controlled documents, supports procedure compliance, and coordinates updates to specifications, design descriptions, verification plans, and test procedure letters with engineering and bomber teams.

Build and maintain Engine X performance dashboards, reporting frameworks, data models, and complex SQL analyses using Snowflake. Track card, booking, rewards, spending, and retention metrics; investigate anomalies; support A/B tests; document metric definitions; and communicate findings to product, finance, and leadership. Collaborate with analytics and data engineering teams to validate pipelines and improve data quality.

Performs data profiling, quality analysis, governance, metadata and lineage management, and Master Data Management support. Collaborates with data owners, stewards, business stakeholders, and technical teams to resolve issues and improve governance processes. Maintains glossaries, dictionaries, controls, metrics, and reports; supports enterprise data initiatives, communications, training, and stakeholder adoption. Provides guidance to less experienced analysts while applying governance standards and documenting business requirements.