Top Hybrid Data Analysis Jobs

Leads advanced marketing analytics initiatives, manages and mentors an analytics team, develops statistical and machine learning models, and builds marketing mix, attribution, forecasting, and campaign measurement frameworks. Partners with clients, account teams, Business Intelligence, Data Engineering, and vendors to translate business challenges into actionable insights and optimize media investment. Requires hands-on programming, data wrangling, regression, client communication, and leadership experience in an agency or consulting environment.

Analyzes spatial and tabular data for planning, engineering, and infrastructure projects. Creates maps, cartographic exhibits, dashboards, web applications, and spatial datasets; performs geoprocessing and quality control; maintains GIS databases, metadata, and documentation. Provides GIS training and technical support while collaborating with project teams. The role requires ArcGIS proficiency and familiarity with geodatabases, with Python, CAD integration, enterprise GIS, and imagery processing preferred.

Analyze catastrophic insurance claims data and validate financial and uncertainty models using statistical methods, simulations, and code in R or C++. Document methodologies, assess model accuracy, create visualizations and presentations, and communicate technical findings to internal and client-facing teams. The role focuses on catastrophe risk, probability, insurance concepts, and quantitative modeling.

Leads quantitative and qualitative research projects from design through publication, focusing on employer health benefits surveys. Responsibilities include survey sampling and programming, data analysis, coding and documentation, vendor and respondent coordination, literature reviews, report writing, media and stakeholder responses, and creating data visualizations for nontechnical audiences.

Leads the Audience Analytics team, develops staff, prioritizes analytics resources, and delivers insights supporting audience growth, fundraising, retention, engagement, revenue planning, and organizational decisions. Oversees data integration, analysis, dashboards, forecasting, governance, and reporting. Partners with cross-functional leaders to define measurement strategies, translate complex findings into recommendations, improve analytics infrastructure, and manage external vendors. Requires strong SQL, business intelligence, stakeholder communication, people leadership, and analytical quality assurance skills.

Analyze and model marketing, product, and loan application data to optimize the borrower funnel and drive growth. Build BigQuery datasets, dbt models, and Tableau dashboards; evaluate customer behavior, acquisition costs, approval rates, and origination performance. Partner with Product, Marketing, and Engineering on A/B tests, statistical analysis, and actionable insights for leaders. Apply lending and fintech knowledge to improve conversion, customer value, and portfolio outcomes.

Build and manage enterprise datasets, reports, dashboards, analytical tools, and automated data pipelines. Combine data from multiple systems, write SQL, conduct ad hoc analyses, and partner with technology and data engineering teams to operationalize solutions. Collaborate with stakeholders across product data, merchandising, marketing, and finance, communicate findings to technical and executive audiences, and help establish analytics tools, processes, and methodologies.

Own product analytics for Heartflow’s platform by measuring adoption, retention, utilization, and feature impact. Design experiments and quasi-experimental analyses, establish product metrics and event taxonomies, build dashboards, and partner with Engineering on instrumentation. Translate quantitative and qualitative customer insights into product and commercial recommendations. Champion AI-enabled analytics, ensure data quality and compliance in a regulated medical-device environment, present findings to leadership, and mentor analysts.

Analyze exchange datasets across equities, FX, options, and futures; develop liquidity and order-book metrics; and create commercial, client-ready data products. Apply statistical and machine learning methods to identify patterns, anomalies, and predictive signals. Partner with engineering, sales, marketing, internal teams, and clients on data ingestion, normalization, cloud distribution, product specifications, competitive analysis, and market-data commercialization.

Collects, cleans, validates, and analyzes data from multiple sources. Develops dashboards, reports, and visualizations using SQL, Excel, Power BI, or Tableau. Identifies trends, monitors data quality, supports KPI tracking, and delivers actionable insights for business decisions. Collaborates with stakeholders, documents analytical processes, prepares regular and ad hoc reports, and recommends process improvements based on data.