Top Hybrid Data Analysis Jobs

Evaluates analytical and fraud models, compares performance, prioritizes models for implementation, and coordinates deployment into production. Manages timelines, requirements, dependencies, deliverables, and issue resolution across data science, technology, modeling, and business teams. Tracks model performance before and after implementation, analyzes results, prepares reports, and communicates recommendations to stakeholders.

Leads client-facing survey analytics engagements from research design and advanced analysis through insights and client-ready deliverables. Applies statistical testing, regression, segmentation, MaxDiff, and Conjoint methods; ensures data quality and analytical standards; communicates findings to technical and senior audiences; and partners with product, technology, design, and research teams to productize analytics solutions.

Leads data strategy, advanced analytics, data quality, governance, visualization, and automation initiatives supporting fulfillment-center capacity planning. Translates complex business challenges into actionable insights, mentors analytics professionals, collaborates with senior stakeholders, and drives measurable operational improvements through predictive analytics, data modeling, and effective data storytelling.

The Senior Data Analyst identifies and validates data sources, performs data quality assessments and cleansing, applies statistical and exploratory analysis, and develops stakeholder-focused visualizations. The role translates business problems into data-driven solutions, collaborates cross-functionally, supports data governance, and mentors junior analysts. Required tools and technologies include SQL, Python, Matplotlib, and Tableau, with familiarity in big data, data architecture, and machine learning applications.

Provides GIS mapping, spatial analysis, cartographic production, web maps, dashboards, and geospatial data management for environmental and multidisciplinary projects. Supports field data collection, quality assurance, data conversion, technical troubleshooting, project deliverables, and collaboration across offices. Uses Esri ArcGIS platforms to analyze and present spatial information, mentor colleagues, and deliver client-focused geospatial solutions.

Designs and implements technology solutions using large, complex data sets to address scientific and business problems. Responsibilities include data integration, visualization, analysis, software development, data warehousing, statistics, and machine learning. The role develops novel insights, advances technical capabilities, mentors others, authors publications, collaborates across disciplines, and ensures compliance with corporate, GxP, safety, and data security standards.

Operate and improve data pipelines supporting construction equipment intelligence. Monitor scrapers and data feeds, diagnose failures, maintain quality gates, manage public-records acquisition and vendor relationships, and conduct SQL-based analysis for dealers and founders. Perform lead-quality reviews, document data sources, coordinate county outreach, and identify silent data failures. The role requires strong SQL, Python, spreadsheet, operational, communication, and AI-assisted workflow skills in an autonomous startup environment.

Manage, evaluate, maintain, analyze, and deliver environmental datasets throughout project lifecycles. Use EQuIS, Excel, and related tools to ensure data quality, develop workflows, troubleshoot issues, create reports and visualizations, and support multidisciplinary technical teams. Collaborate with scientists, engineers, geologists, clients, and project managers while mentoring junior staff and improving data efficiency and consistency across projects.

Own audience intelligence and engagement analytics across website, email, events, and acquisition channels. Build KPIs, reporting, segmentation, and re-engagement strategies to improve retention, engagement, and purchases. Reconcile data across CRM, enrichment, and email platforms; triage data issues; analyze behavioral trends; and translate insights into actionable strategies. The role also requires cross-functional collaboration and effective use of AI and agentic tools.

Volunteer lead responsible for managing a team of volunteer data analysts, overseeing precinct-level voter file and turnout data cleaning and analysis, producing standardized precinct reports and strategic recommendations for PCOs, maintaining project tracking systems, and ensuring data security while supporting voter engagement and GOTV strategies.

Monitor payment, fraud, and risk metrics across iLottery and iGaming businesses. Analyze transaction performance, investigate anomalies and fraud events, identify data-quality issues, produce reporting, and recommend operational improvements and cost savings. The role uses Excel, business intelligence platforms, AI, and machine learning techniques to improve detection capabilities, maintain controls, support payment providers, and communicate findings to leadership.

Build and enhance a global corporate hierarchy framework by defining entity relationships, validating parent-subsidiary linkages, establishing governance controls, and improving data quality. The role analyzes large datasets, supports banking and regulatory use cases, collaborates with business, product, and engineering teams, and contributes to project delivery, stakeholder communication, and executive reporting.