Top Data & Analytics Jobs

The Lead Digital Product Analyst will drive site performance analytics, partner with cross-functional teams, and create actionable insights to improve eCommerce strategy.

Conduct research pushing experimental and causal-methodologies in public opinion, develop tools and prototypes to analyze experimental data, and communicate findings to internal teams and clients to inform platform features and insights.

Lead data workstream for complex implementations: collect, validate, transform and upload large datasets into VMS, perform ETL and rate audits, ensure data quality and governance, mentor junior analysts, and communicate status to clients and stakeholders.

Lead design, build, and optimize scalable ELT/ETL pipelines and data architectures to support analytics and filing-ready statistical reporting. Partner with Actuarial and Compliance, ensure data quality, mentor engineers, and introduce tooling and best practices.

Build and maintain KPI reporting and dashboards for wallet, loyalty, and remittance performance across markets. Produce recurring and ad-hoc analyses (SQL, Sheets, BI tools), surface underperformance signals, support root-cause analysis, and translate findings into operational recommendations. Partner with Product Ops and data engineering to formalize recurring analyses and support GTM readiness metrics. Monitor industry trends and provide executive-level reporting used by the Director to brief the COO and exec team.

Perform end-to-end analytical projects: source, clean, analyze, and synthesize data to answer commercial and operational questions. Communicate findings to investment teams and portfolio leadership, partner with data science and engineering, build reusable tools, and apply GenAI to accelerate workflows.

Serve as the bridge between Finance/Accounting and IT to translate requirements into ERP/financial system solutions. Lead process harmonization, data governance, cleansing, migration and reconciliation, and identify automation/reporting improvements. Support vendor evaluations, UAT, training, change management, and stakeholder engagement to drive system adoption and operational readiness.

Produce and publish weekly and monthly global forecasting reports (sell‑in/sell‑out), monitor KPIs, maintain demand planning master data, identify trends/variances, automate reporting, support cross‑functional forecasting projects and ad‑hoc senior management analysis.

Design, develop, maintain, and execute complex financial models for loss forecasting, stress testing, pricing, originations/collections, and portfolio optimization. Use Python or R (and SQL/SAS/other languages) for data processing and model development, build Power BI analytics, collaborate with business partners and regulators, support model validation/audits, research industry/academic methods, and develop data environments to support quantitative activities.

Lead enterprise data discovery, inventory, classification and governance initiatives. Evaluate and run POCs for tools (OneTrust, BigID, Varonis, Cyera, Delphix, RecordPoint, Collibra, Microsoft Purview). Conduct stakeholder workshops, assess classification accuracy, security, scalability, integrations, and metadata flow. Produce recommendations, feasibility assessments, roadmaps, and support Collibra integration.