Top Senior Analytics Jobs in Dayton, OH

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

Lead the design and operation of automated compliance monitoring for consumer lending: translate regulations into rule-based data checks, own exam and audit data requests, triage exceptions, drive automation, steward compliance data, and provide technical mentorship to a supporting analyst. Produce audit-ready, reproducible evidence for regulators, bank partners, auditors, and senior leadership.

Lead independent validation and governance of credit and fraud models, build automated Python monitoring for model drift and performance, drive remediation with model developers, and liaise with audit and regulators to support Affirm Bank's model risk management.

Design and maintain people analytics reporting, dashboards, and data models; perform advanced statistical analyses and survey design; automate workflows and collaborate with stakeholders to translate insights into actionable recommendations.

Lead revenue-cycle performance analyses, diagnose root causes, quantify value (ROI/collections lift), and translate findings into pragmatic, stakeholder-ready recommendations. Partner cross-functionally to scope analyses, validate data, and drive strategic workstreams that inform product roadmap and client outcomes.

Lead and build a product analytics function: define KPI framework, instrumentation, and self-serve analytics using Pendo and BI tools. Partner cross-functionally to measure product performance, surface insights, influence roadmap and embed AI-powered analytics into product lifecycle.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead a team to analyze sales data, build and maintain Power BI and Excel reporting, leverage AI and automation for pipeline and lead scoring, align cross-functional GTM strategies, ensure data quality, and deliver actionable, executive-ready insights to drive sales performance and quota attainment.

Lead analytics modernization efforts by migrating SAS workflows to R/Python, establishing validation and reproducibility standards, implementing CI/CD and version control, mentoring teams, and supporting cloud-based scalable analytics platforms for public health and research environments.

Design, build, and maintain scalable ETL/ELT pipelines and analytics-ready data models using Python and SQL. Implement GitLab CI/CD, develop dashboards in Tableau/Power BI, perform data cleaning and analysis, support modeling and AI initiatives, document metadata, and mentor junior staff while collaborating with cross-functional teams to deliver actionable insights.

Leads and develops an analytics engineering team that builds data pipelines, analytical models, reporting, and scalable data infrastructure. Partners with Product, Engineering, Growth, and Operations to deliver reliable, actionable data. Establishes governance, quality, testing, documentation, and modeling standards while prioritizing analytics projects and communicating with stakeholders.

Lead analytics and data science initiatives to drive measurable business outcomes across various functions, including Underwriting and Claims. Oversee the full analytics lifecycle, foster stakeholder engagement, and mentor junior team members.

Designs and delivers a global analytics platform supporting reporting, visualizations, self-service analytics, and embedded data products. Responsibilities include data collection and processing, semantic modeling, warehouse and pipeline development, query optimization, governance, analytics enablement, and stakeholder collaboration. The role provides actionable insights from complex travel data and builds integrated analytics applications using cloud platforms and business intelligence tools.

Analyzes healthcare claims, provider, reimbursement, and financial data to support out-of-network dispute negotiations, arbitration, QPA accuracy, and IDR performance. Builds SQL-based reports, dashboards, data processes, metrics, and financial views; validates data quality; integrates internal and external sources; identifies trends and risks; and presents actionable recommendations to leadership and cross-functional stakeholders.

Provide insights and recommendations to improve end-to-end purchase customer journeys across web and app for B2C and B2B. Lead A/B testing and experimentation, ensure accurate data collection and impact measurement, build self-service reporting and visualizations, query and process data, and present findings to stakeholders and senior leadership.

The Senior Analyst will lead digital measurement analytics for emerging payments platforms, including data collection, validation, reporting, and feature performance measurement. Responsibilities include partnering with marketing, technology, digital, and analytics stakeholders; delivering accurate, compliant projects; communicating insights; supporting strategic priorities; and developing analytics roadmaps. The role requires hands-on problem solving, visualization, web analytics, and collaboration across Agile teams.

Builds and maintains analytical data foundations for lending, underwriting, pricing, originations, collections, and portfolio analytics. Develops reusable SQL assets, dimensional models, data marts, transformation workflows, reporting solutions, and business intelligence products using SQL, Python, dbt, Git, Snowflake, Power BI, and Sigma. Partners with technical teams, analysts, and business stakeholders to integrate data, standardize metrics, automate testing, and deliver reliable, documented, scalable analytical assets.

Design, build, and maintain enterprise Power BI dashboards, data models, and ETL workflows. Perform statistical and geospatial analyses, ensure data quality and governance, translate stakeholder needs into KPIs and reports, mentor junior analysts, and present insights to technical and non-technical audiences to support public health and government programs.

Leads data and analytics engineering for Zero Trust maturity assessment and implementation measurement. Designs common data models, integrates and validates enterprise data, develops maturity and risk metrics, supports prioritization and gap analysis, and establishes data quality, lineage, traceability, and documentation practices. Partners with dashboard and automation specialists to streamline reporting and data refresh workflows.

Build and maintain data infrastructure, integrate veterinary partner systems, develop dbt models and pipelines, provide analytics modeling, testing, reporting, and deliver actionable insights to customers and internal teams.

Design and build scalable data foundations, pipelines, semantic models, and AI-grounded tooling. Lead platform-level AE tooling, reusable dbt patterns, observability, cost strategies, and agentic AI workflows. Partner with stakeholders, guide team technical development, and drive cross-functional data initiatives from ambiguous problems to production.

Lead design and delivery of Snowflake-centric cloud data platforms. Engage with clients to gather requirements, architect scalable secure solutions, provide technical leadership, develop roadmaps, advise executives, and guide implementation best practices across the analytics stack.

Design and implement end-to-end data solutions on Microsoft Fabric and Azure for insurance datasets. Build ingestion pipelines (batch, streaming, API), Lakehouse architectures, and data models. Enforce governance, security, compliance, and cost/performance optimizations while guiding engineers and stakeholders on architectural best practices.