Top Data & Analytics Jobs

Leads the Commercial Analytics function and advises Sales and executive leadership through performance reporting, forecasting, financial modeling, pricing analysis, profitability optimization, market analytics, and strategic planning. Manages analytics personnel, establishes reporting standards, develops business insights, and partners cross-functionally with Finance, Sales Operations, Marketing, Product Management, and Operations to support profitable growth and data-driven decisions.

Manages program reporting for AECOM’s Program Management team. Owns Power BI reporting, develops dashboards and scorecards, consolidates data from project, cost, schedule, document, and risk systems, establishes KPIs, analyzes trends, and provides actionable insights to leadership and stakeholders. Ensures reporting accuracy, consistency, and data integrity while improving reporting standards and facilitating communication across project teams.

Full-time SAP internship supporting HanaHaus business insights. Responsibilities include building automated dashboards and reports, conducting financial forecasting, tracking product utilization, automating finance processes, analyzing data from multiple sources, preparing leadership presentation materials, and contributing to strategic projects. The role requires Python, SQL, Excel, strong communication, and customer-oriented problem solving.

Supports San Francisco city departments through policy, budget, finance, contracts, grants, and data analysis. Duties may include analyzing datasets, developing reports and dashboards, tracking revenues and expenditures, preparing budget and contract documents, monitoring compliance, supporting grant applications, and developing recommendations for operational and policy decisions. The role requires collaboration with department staff, vendors, stakeholders, and elected officials.

Senior Decision Scientist partners with product, engineering, marketing, and finance teams to guide roadmaps, resource allocation, and business strategy. The role uses experimentation, causal inference, statistical analysis, metric strategy, and user behavior research to produce actionable recommendations. Responsibilities include establishing causality, improving instrumentation, communicating insights to leadership, and using AI tooling to scale analytical workflows. The position requires consumer technology analytics experience, strong SQL and Python or R skills, and expertise in experimentation and causal inference.

Analyzes tolling, bypass, device, and customer data to produce actionable business insights. Builds and maintains Power BI reports, dashboards, semantic models, and DAX measures; validates data quality, troubleshoots refresh issues, and documents reporting assets. Responds to stakeholder requests, gathers requirements, explains findings, and improves BI workflows. Uses AI-assisted analytics tools while validating outputs for accuracy and policy compliance.

Designs and leads enterprise data pipelines and integrations across Snowflake, Oracle Fusion, on-premises databases, and cloud applications. Ensures data quality, governance, security, scalability, and performance while supporting Power BI, AI/ML, and self-service analytics. Partners with business and technical stakeholders, leads migrations, mentors engineers, optimizes data platforms, and establishes engineering best practices.

Own revenue forecasting models, pipeline analytics, and commercial performance insights across a global flexible-workspace network. The role integrates data from Salesforce, Looker, Snowflake, and spreadsheets; analyzes pricing, conversion, sales velocity, unit economics, and marketing and sales efficiency; partners with Finance and commercial leaders on budgets and planning; and communicates findings through actionable memos and presentations.

Design and operate end-to-end infrastructure for intracortical neural data, from ingestion and validation through preprocessing, versioned dataset releases, and training data loaders. Preserve scientific metadata and provenance while implementing signal processing, quality checks, storage optimization, parallel processing, and monitoring. Collaborate with neuroscience, machine learning, infrastructure, and IT teams to support scalable, reliable model training and sensitive research-data management.

Leads enterprise data engineering, analytics, architecture, and AI solution delivery. Oversees teams, EDW and data lake architecture, Informatica pipelines, BigQuery data models, Tableau reporting, governance, security, quality, operational reliability, roadmaps, budgets, and stakeholder partnerships. Requires strong technical leadership, business translation, and hands-on expertise across data integration, warehousing, analytics, and governed AI solutions.