Top Data & Analytics Jobs

Perform advanced pricing and trade analysis for the Grocery segment, using multiple data sources to guide list pricing, promotions, and investments. Analyze market trends, margins, competitive pricing, volume, and promotional tactics to identify risks and opportunities. Translate data into recommendations and leadership presentations, build reporting frameworks, collaborate cross-functionally, and lead pricing process and tool initiatives.

Analyze complex financial and business data to guide planning, forecasting, investment decisions, and strategic growth. Partner with FP&A, Accounting, RevOps, Product, Marketing, Data Engineering, and analytics teams; automate recurring workflows; build self-service dashboards and data assets; improve analytics infrastructure; and communicate actionable insights to technical and non-technical stakeholders.

Investigate offline and direct mail channel performance, attribution, vendor data, and measurement methodologies. Build response, lift, allocation, and regression models; manage direct mail testing data pulls and mail merges; create KPI dashboards; and communicate actionable recommendations to marketing stakeholders. The role requires proactively identifying opportunities, validating data and vendor claims, and translating complex analytical findings into business decisions.

Analyze social media and review data to identify sentiment trends, root causes, and customer experience issues. Model the financial impact of poor experiences on sales, returns, churn, and subscription renewals. Build dashboards and executive presentations, recommend improvement investments, and track initiative outcomes. Support customer responses on social channels while partnering with Product, Marketing, Finance, and Customer Care to improve satisfaction and brand reputation.

Own digital analytics, reporting, dashboard development, data extraction, ETL, and AI-enhanced insight generation for luxury e-commerce. Partner with business leaders and online retail teams to translate questions into analysis, identify trends and opportunities, improve KPIs, and create self-service reporting. Present clear recommendations to leadership, maintain data governance, validate AI-generated insights, and support data and AI initiatives.

Supports geospatial services for renewable energy projects by maintaining geodatabases, conducting spatial analyses, creating publication-quality maps and permitting exhibits, integrating GPS, aerial imagery, and drone data, and documenting data quality and metadata. Collaborates with engineers, environmental scientists, project managers, and senior GIS analysts while gaining practical experience in site selection, constraints mapping, and permitting deliverables.

Lead advanced product analytics for a consumer product team by analyzing complex data, designing experiments, applying statistical and causal inference methods, developing metrics and reporting tools, and delivering actionable recommendations to cross-functional stakeholders and senior leadership. The role requires strong Python or R and SQL skills, product analytics experience, AI-assisted analytics proficiency, and the ability to influence product strategy.

Analyze internal and external data to identify trends, build targeted datasets for omnichannel marketing campaigns, and provide product, customer, segment, and business-unit recommendations. Develop and implement statistical response, performance, and lookalike models using Python and R. Create KPIs from multiple data sources and collaborate with internal teams to support campaign performance and decision-making.

Develop and maintain BI dashboards, data models, ETL processes, integrations, and data quality reporting using Power BI, Tableau, GoodData, Excel, and SQL. Translate stakeholder requirements into reporting solutions, monitor and resolve data issues, support Workday-Kantata integrations, manage PSA reporting and uploads, and provide profitability, pricing, project, and resource analyses. Create documentation and training while ensuring reporting accuracy, data integrity, and business SLA compliance.

The Senior Data Analyst serves as a bridge between business stakeholders and enterprise data platforms. Responsibilities include defining KPIs, analyzing customer and commercial data, building dashboards and reporting solutions, developing SQL and Python data transformations, managing pipelines, integrating enterprise systems, and establishing data governance and quality standards.