Top Hybrid Data Analysis Jobs

The Economist will analyze travel and spending data to identify trends, craft insights, and present findings, serving as an economic advisor to leadership.

Leads business and system requirements gathering, stakeholder solutioning, documentation, configuration, troubleshooting, quality assurance, testing, and release-note coordination. The role supports customization requests, reviews configurations, oversees project testing, monitors junior business analysts, and helps deliver solutions for fintech and financial-services clients.

Lead advanced risk, fraud, and payment optimization analyses for major fintech merchants. Analyze large-scale transactional, ML output, and labeled risk data; design experiments and statistical investigations; develop scalable analytical tools, ETL workflows, dashboards, and reusable frameworks; collaborate with risk product teams; translate findings into merchant strategies and product improvements; enable commercial stakeholders through playbooks and self-service tools; and mentor analysts.

Develop Python and Excel models for life insurance product calculations, validate system values, define requirements, support product launches and system conversions, analyze defects, and maintain data integrity. The role applies actuarial and statistical methods, improves workflows through automation, coordinates shared model development, and communicates technical findings and deliverables to cross-functional business, systems, operations, legal, compliance, and vendor partners.

Design and maintain billing data systems that reconcile patient engagement data, codify auditable billing logic in BigQuery SQL, automate data cleanup with Python or Google Sheets scripting, and generate accurate, version-controlled invoice files. Investigate mismatches and edge cases, document workflows, and collaborate with Finance, Sales, Engineering, and Product to improve billing inputs and processes.

Analyzes complex business and technology problems across integrated financial technology platforms. Creates requirements documents, diagrams, user stories, acceptance criteria, and test plans; coordinates dependencies and delivery across agile product teams. Uses SQL, Tableau, R Studio, SAS, and integration tools to validate data, perform statistical modeling, document APIs and workflows, identify process gaps, and produce dashboards supporting operational improvements.

Analyze transaction enrichment product performance, data quality, accuracy, match rates, and other metrics. Investigate anomalies in large datasets, build dashboards and automated alerts, improve QA processes and workflows, and develop documentation and monitoring standards. Partner with Product, Engineering, and AI/ML Data Science teams to translate insights into product improvements and automate recurring analytical work.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

As a Senior Data Scientist in Product Analytics, you will analyze data to guide product decisions, support product managers, and improve financial stability for users.

Provide accurate valuations and risk assessments for single-family homes using internal tools and pricing model outputs. Incorporate local market knowledge, collaborate with sales, homes, data science and engineering to improve pricing operations and ensure competitive, consistent offers.