Top Data & Analytics Jobs

The Data Analyst Supervisor leads a team to provide data-driven insights, oversees projects, ensures data accuracy, and collaborates across departments for strategic decision-making.

Collects, analyzes, validates, and interprets large datasets to support strategic decisions. Develops reports, dashboards, visualizations, data collection systems, and automated analysis processes. Identifies data quality issues, ensures governance compliance, presents actionable insights, and supports process, organizational, product, and IT system improvement initiatives.

Owns production data systems end to end, including data models, ETL and API integrations, applications, platform maintenance, data quality, governance, and technical debt. Supports OPSDB and exploration operations, improves reliability and alerting, documents systems, collaborates with cross-functional and nontechnical stakeholders, and mentors junior analysts. The role also supports procurement and inventory initiatives, works with geologists, and requires occasional international travel to exploration sites.

Collects and analyzes internal and external data to identify trends, opportunities, and risks. Develops dashboards, reports, and visualizations for leadership; monitors KPIs; partners with advisors to answer business questions; and supports strategic planning through forecasting, modeling, and scenario analysis.

Analyze large relational datasets, develop optimized SQL, validate data quality, troubleshoot discrepancies, maintain ETL pipelines, automate workflows with scripts and scheduling tools, and produce recurring reports and dashboards that support leadership decision-making in a controlled data environment.

Analyze and validate data from multiple sources, build automated dashboards and ad hoc reports, perform statistical testing, and provide insights that support business decisions. The role collaborates with data engineering and business teams, maintains data systems, improves data quality, identifies new data sources, and helps define the data initiative roadmap.

Analyze data using SQL within financial services, with a focus on Anti-Money Laundering (AML). Candidates must be local to New York City and available for a two-month contract, with phone and in-person interviews. Experience or knowledge of FCRM is a plus.

Collects data from applicable systems, gathers requirements for forms and charts, analyzes data, creates visualizations, maintains databases, assists with software validation, and develops training materials. Requires strong Microsoft Office skills, communication abilities, and SAS experience, with Statistica and JMP preferred.

Design and build a modern R&D analytics platform to replace legacy reporting infrastructure. Develop SQL-based data pipelines, transform multi-source data, create KPI workflows and analytics interfaces, and generate actionable insights. Use AI coding tools while rigorously reviewing, testing, and validating outputs. Establish data-quality monitoring and governance frameworks, optimize platform performance, and collaborate with R&D and operational stakeholders.

Analyzes and maintains healthcare data exchanges between the company and external partners. Responsibilities include designing EDI mappings and transformations, validating claims and eligibility data, resolving errors, monitoring data feeds, supporting integrations, documenting processes, generating performance reports, and identifying automation opportunities. The role requires healthcare EDI expertise, knowledge of claims transactions and HIPAA compliance, technical troubleshooting, and collaboration with internal teams and trading partners.

Support client projects by structuring business problems, assessing data, selecting analytical approaches, conducting analyses, building and validating models, and translating findings into recommendations. The role involves quantitative consulting across industries, collaboration with clients and project teams, and potential work in AI, credit risk, sustainability, optimization, GenAI, and supply chain analytics. Business fluency in German and English and willingness to travel are required.

Supports client projects by structuring analytical problems, assessing data, selecting analytical methods, conducting analyses, building and validating models, and translating results into recommendations. Work may involve AI, predictive modeling, portfolio decarbonization, credit risk, optimization, chatbots, and supply-chain analytics. The role also includes client collaboration, communicating complex concepts clearly, and contributing to project teams across industries.

Lead and mentor a team of analysts to deliver HR-related analytics and BI solutions. Mine and model large datasets, design tests, improve reporting and operational efficiencies, and collaborate across business units to inform strategy and product decisions.

Develop and maintain manufacturing data infrastructure, databases, dashboards, and analytical tools integrating fab, equipment, metrology, test, yield, and reliability data. Build Python and JMP workflows, automate reporting and alerts, ensure data traceability and quality, troubleshoot dashboard and data-connection issues, and support SPC, DOE, process capability, reliability, and root-cause analyses. Collaborate with engineering, manufacturing, quality, reliability, and IT teams.

Drive growth and product decisions through experimentation, statistical analysis, metrics management, data pipelines, modeling, and dashboard development. Partner with business and product teams to answer analytical questions, build ingestion and transformation workflows with dbt, and create visualizations that enable stakeholders to explore data and act on insights.

Analyze fundraising data by building reports, dashboards, data pulls, forecasts, and operational metrics. Clean and validate Salesforce and related data, identify quality issues, document standards, and support finance reconciliation. Build lightweight tools and workflows using spreadsheets and Airtable, ensuring important data flows into Salesforce. Partner cross-functionally on reporting architecture and coach fundraisers on effective system use.

Analyze large-scale electronic health record and real-world data using SQL, R, and Python. Scope requests, produce research studies and results, write Databricks SQL regex queries, support customers, investigate data sources, collaborate on peer-reviewed publications, and create enablement materials for researchers.

Leads data discovery, profiling, quality assessment, and Source-to-Target Mapping for wealth management data platforms. Analyzes complex financial datasets using advanced SQL, documents business rules and transformations, translates requirements for ETL and data engineering teams, supports data governance and testing, and communicates findings to technical and business stakeholders.

Manages healthcare data exchange operations, including EDI mapping, file transformation, validation, monitoring, troubleshooting, error resolution, partner onboarding, reporting, and process automation. The role supports medical, dental, and vision claims data while ensuring HIPAA compliance, data accuracy, and secure transfers. It collaborates with internal teams, clearinghouses, employers, providers, and third-party administrators to resolve issues and improve data integration processes.

Lead a team delivering enterprise-wide model risk reporting and AI-driven automation. Build and deploy scalable ML/AI solutions, conversational reporting, multi-agent workflows, and centralized data integrations. Drive analytics strategy, validate models and data, improve reporting and operational efficiency, and collaborate across business units.

Analyze and visualize digital channel performance, build dashboards in Power BI, consolidate multi-vendor data, apply AI agents and tools to automate reporting, derive insights to optimize marketing spend across DSP, loyalty, and CRM channels, and forecast performance to inform strategy.

Analyzes workforce data to guide hiring, retention, organizational design, and people-program decisions. Builds dashboards, reports, data models, pipelines, and governance practices; ensures HR data integrity; automates reporting; identifies workforce trends and risks; and partners with People, Finance, HRIS, engineering, and business leaders to deliver actionable insights.

Build and maintain data pipelines using ETL/ELT, Databricks, Python, Spark, and Airflow. Manage data transformations, databases, schemas, and data quality controls. Support reporting, analytics, and machine learning integrations while deploying solutions in AWS. Automate workflows, troubleshoot data issues, document processes, and collaborate with data scientists, analysts, database administrators, and business stakeholders.

Interns will code software to automate processes, scrape and collect large datasets, and conduct advanced econometric analyses to investigate fraud across finance, healthcare, and cryptocurrency domains. The role involves individual and team projects, applying data science and econometric techniques, and translating academic knowledge into real-world consulting and forensic analytics applications.

Analyzes fraud across finance, healthcare, and cryptocurrency domains using data science and econometric techniques. Responsibilities include coding process automation software, scraping and collecting large datasets, and conducting advanced econometric analysis. The intern collaborates on individual and team projects while applying quantitative academic skills to real-world investigations.