Top Data & Analytics Jobs

Analyzes large, complex datasets using Python, R, SQL, statistical techniques, modeling, and automation. Develops analytical tools, reports, and automated solutions; identifies trends; translates findings into business recommendations; presents insights to technical and business audiences; and partners across teams to measure results and improve solutions.

Owns the enterprise data quality framework, Critical Data Element methodology, quality thresholds, scorecards, and remediation processes. Independently assesses master data quality, performs root-cause analysis, tracks issues to closure, and communicates trends and business impact to senior leadership and the Board. The role requires strong SQL and analytical skills, enterprise data quality program ownership, and the ability to quantify the cost of poor data quality.

Owns the enterprise data quality framework across multiple domains, including Critical Data Element methodology, quality thresholds, Board-level scorecards, trend reporting, and remediation oversight. The role independently assesses master data quality, drives root-cause analysis, and translates data quality performance into business risk, cost, and operational outcomes. It requires strong SQL and analytical skills, executive communication, and experience managing enterprise data quality programs.

Performs data quality and quality assurance functions for critical reference data, ensuring accuracy, validity, and adherence to data conventions. Manages control framework findings, supports issue resolution, coordinates with global operational teams, and escalates complex processing issues. Contributes to projects, User Acceptance Testing, Monthly Control Assessment testing, corrective action plans, audits, and regulatory compliance activities.

Supports alternative investment fund services through data analysis, workflow documentation, data pipeline and data model understanding, data governance, quality scorecards, dashboards, and reporting. The role queries and analyzes data, helps deploy governance tools, supports internal and external clients, and collaborates with stakeholders to maintain accurate, complete client data and timely deliverables.

Conducts advanced Finance data governance research, analysis, and implementation for regulatory reporting and priority data use cases. Partners with business and technology stakeholders, monitors policy adherence, maintains metadata and lineage artifacts, develops governance reporting and automation tools, and advises senior management on data risks and recommendations. Leads moderate-scope projects, supports audits and controls, and mentors junior team members.

The Senior Data Analyst will source, validate, and reconcile data supporting forecasting, purchasing, inventory planning, and reporting. Responsibilities include auditing forecasts and operational outputs, identifying data quality issues, rating results, automating recurring checks and workflows with AI, documenting planning processes, and integrating tools with merchandising and operating systems. The role collaborates with planning, merchandising, sourcing, logistics, eCommerce, wholesale, and finance teams to deliver reliable, decision-ready data.

Supports daily reporting by preparing recurring Excel reports, extracting data from ERP systems, cleaning and validating information, tracking metrics, responding to ad hoc requests, documenting processes, and improving reporting efficiency. The role works with Operations, Finance, Sales, and Leadership and is intended for candidates with 0–2 years of experience, including recent graduates.

Conducts complex data coordination and analysis projects for the Reporting, Analytics, & Data team. Responsibilities include querying and transforming datasets, creating reports, publications, presentations, dashboards, and visualizations, interpreting findings for technical and non-technical audiences, and maintaining technical documentation. The role also coordinates multiple projects, communicates with diverse stakeholders, and travels approximately 15–20 overnights annually.

Leads enterprise data management strategy, data governance, quality frameworks, master data management, operational oversight, and a team of data analysts. Oversees data integrity, metadata, lineage, controls, incident remediation, vendor coordination, reporting, and domain data product health. Partners with business, product, engineering, and governance stakeholders to improve sales, marketing, and CRM data trustworthiness while managing major initiatives, risks, dependencies, and regulatory requirements.

Monitors and reconciles DenialsAI account data to verify case creation, workflow progression, user activity, and appeal output. Investigates pipeline discrepancies, builds operational reports and dashboards, tracks resolution and coverage metrics, maintains KPI scorecards, defines monitoring thresholds, and validates data accuracy. Collaborates with engineering, operations, client services, and external stakeholders while complying with HIPAA and information security requirements.

Analyzes provider performance and compensation data, maintains incentive plan records, reviews contracts, processes incentive payments, supports payroll accuracy, models plan updates, answers provider questions, and assists with SOX compliance audits while meeting strict deadlines.

Maintains data integrity and accuracy within case tracking systems, monitors inbound data feeds, resolves escalated data issues, and develops quality analyses, reports, and performance metrics. Mentors staff, supports agency bureaus with reporting, maintains automated and reproducible analysis tools, administers internal content portals, creates standardized document templates, and researches technology solutions for internal applications.

Lead master data governance for product/material domains across Agile PLM and SAP S/4HANA/SAP MDG. Define governance, document requirements and processes, support MDG design and integrations, drive data migration/cleansing, perform impact analysis, and champion data quality across supply chain, manufacturing, and IT stakeholders.

Develops Power BI dashboards, leads data migration to a new fundraising and ERP system, validates and reconciles data, gathers reporting requirements, builds Power Automate workflows, documents processes, supports staff, and coordinates third-party data integrations. The role requires strong analytics, business intelligence, SQL, data modeling, reporting, and stakeholder communication skills, with approximately five years of experience.

Design and optimize ETL processes, data ingestion systems, streaming applications, and cloud data architectures using SQL, Python, Snowflake, AWS, and Redshift. Maintain and troubleshoot production data pipelines, integrate analytical outputs with business intelligence applications, optimize queries, and collaborate with analysts and engineers using Airflow and Databricks. Evaluate AI tools and emerging technologies to improve data warehouse workflows.

Design and build interactive dashboards and UIs using tools like Qlik Sense, Tableau, or Power BI. Clean, wrangle, and analyze data from warehouses and big-data sources. Define reporting objects, metrics, filters, and visual best practices to deliver actionable insights for DoD clients. Work requires Secret clearance and a bachelor’s degree.

Own growth marketing analytics across acquisition channels, including attribution modeling, incrementality testing, performance dashboards, automated insights, and predictive modeling. Partner with marketing leadership to translate channel data into budget and investment recommendations, uncover growth opportunities, and improve decision-making. Build scalable measurement frameworks and become the subject matter expert for growth data across the organization.

Designs and delivers data-driven audience, targeting, and measurement solutions for digital marketing campaigns. Translates business goals into technical requirements, improves data quality and reporting, standardizes audience documentation, and manages initiative execution, monitoring, issue triage, and alerts. Partners with Marketing, Product, and Technology on platform enhancements while identifying responsible artificial intelligence applications with human oversight, governance, explainability, and measurable outcomes.

Own product analytics and measurement strategy, including KPI definition, experimentation, reporting, executive dashboards, and scalable dbt datasets. Partner with Product, Growth, Engineering, Design, and leadership to guide roadmap and marketplace growth decisions. Conduct product and market analysis, manage technology-category data, research cybersecurity and AI markets, and use LLMs to improve workflows and enrich the product database.

Owns reinsurance data, automation workflows, controls, and analytics supporting billing, settlements, recoverables reporting, and accounts receivable reconciliation. Develops Alteryx and AI workflows, maintains global treaty data in Sapiens, resolves data issues, monitors large-loss reinstatement premium triggers, and supports Ceded Reinsurance, Finance, and FP&A stakeholders. Leads process standardization and transformation initiatives across international reinsurance operations.

Supports exploration data systems, databases, applications, and digital workflows across multiple sites. Maintains data quality, governance, integrations, reporting, dashboards, and data products while assisting with automation, analytics, and AI initiatives. Provides technical support and training, collaborates with stakeholders on process improvement, and helps ensure exploration data is structured, accessible, and AI-ready.

Leads data projects from requirements through release, building Python and SQL pipelines, integrating and validating market data, automating processes, and supporting daily price assessments. Reviews code and data quality, develops assessment algorithms, resolves operational issues, and mentors analysts. Acts as a bridge between Data and Index teams while applying commodity market knowledge and AI coding tools to improve team productivity and reliability.

Analyze and document enterprise data environments for financial services clients, with a focus on Customer and Party Master Data Management. Define data flows, lineage, quality rules, governance models, entity resolution requirements, and MDM implementation roadmaps. Facilitate requirements sessions, collaborate with business and technical stakeholders, and prepare mappings, diagrams, documentation, and presentations. The role requires strong data management experience, financial services knowledge, and proficiency with analytical and documentation tools.

Maintain data holdings and data standards, analyze complex geospatial datasets, transform data, create visualizations, and provide recommendations to improve data strategies and machine learning model development.