Top Data & Analytics Jobs

Owns Sales and Servicing data as a trusted, governed, discoverable, and AI-ready enterprise asset. Defines data standards, quality controls, metadata, lineage, and business definitions while resolving complex data issues. Partners with AI, engineering, product, governance, and business leaders to enable sales effectiveness, client insights, servicing automation, intelligent routing, and self-service use cases. Leads cross-functional decision-making and translates complex data concepts into actionable business recommendations within a regulated financial services environment.

Owns complex GenAI Standards of Care evaluations, reviewing architectures, data sources, testing, controls, and governance evidence. Identifies risks and control gaps, provides remediation guidance, supports governance dashboards, escalates systemic issues, and improves governance processes and documentation. The role partners with technical teams, solution owners, and leadership to ensure GenAI use cases meet enterprise standards and manage data and technology risks.

Owns marketing and go-to-market analytics, KPI definitions, attribution, campaign and sales-play measurement, scoring-model evaluation, dashboards, and weekly leadership reporting. The role reconciles Salesforce, HubSpot, and attribution data; partners with data teams on source-of-truth datasets; and builds AI-powered analytics agents, automated reporting, anomaly alerts, and data-quality processes to guide budget and pipeline decisions.

Analyze go-to-market performance across Sales, Marketing, and Client Success, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and data marts using Salesforce and modern data-stack tools. Own data quality, documentation, BI-as-code contributions, and AI-enabled analytics workflows. Partner with stakeholders to turn ambiguous business questions into actionable recommendations and deliver results in agile two-week sprints.

Maintain global ERP master data, item and branch records, BOMs, planning parameters, MRP data, and supply chain documentation. Analyze data quality issues, support reporting and dashboards, ensure compliance with SOX and GMP requirements, and collaborate with Manufacturing, Quality, Regulatory, Finance, and planning teams. The role also contributes to process improvements, ERP enhancements, and transformation initiatives.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Develops Python data pipelines and business data objects for applications. Designs, implements, tests, and deploys software and CI/CD pipelines, performs source-to-target mapping, resolves complex technical issues, and promotes software quality practices. The role requires collaboration across functional teams, independent execution of complex assignments, and experience with cloud platforms, Snowflake, version control, and AI coding tools.

Develop causal economic analyses using Mastercard and public datasets. Translate business questions into empirical designs, apply econometric and machine learning methods, lead projects from data preparation through validation, guide causal inference practices, prototype scalable analytics, and communicate findings to clients, stakeholders, and nontechnical audiences.

Designs reusable data ingestion and transformation components, automates data quality, governance, testing, lineage, and deployment workflows, and improves pipeline observability and reliability. The role supports monitoring, incident response, cloud and container integrations, infrastructure as code, documentation, reusable datasets, and Agile platform improvements. Candidates need five or more years of data engineering experience plus expertise in orchestration, distributed processing, storage, scripting, automation, and version control.

Manages a data analytics team delivering complex analysis, forecasts, reports, dashboards, and business insights. Integrates data from multiple sources, defines data quality standards, audits reporting accuracy, and identifies operational improvements and strategic opportunities. Leads high-visibility projects, develops analytical specifications and presentations, communicates findings to senior management, and coaches team members on analytical quality and methodology.