Top Senior Analytics Jobs in Dayton, OH

The Director, Research - Power Markets is responsible for leading the QA/QC process for long-term forecasting, advising leadership, and ensuring market insights are effectively integrated into forecasts.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead retail analytics to identify growth and efficiency opportunities, build strategic recommendations (store footprint, pricing, omnichannel), conduct market/competitive research, drive cross-functional initiatives, and deliver executive-ready analyses and frameworks to inform retail and digital strategy.

This role drives data-driven decision-making in product analytics, collaborating with cross-functional teams to generate actionable insights and evaluate new launches to enhance platform growth.

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.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

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.

The analyst will own planning for launches, build forecasting models, partner with stakeholders, and drive data-driven decisions using AI and analytics.

Designs, builds, and operates ELT data pipelines and analytical datasets for Platform Analytics. Curates and models source data into conformed datasets, ensures performance, reliability, and cost efficiency, contributes to target-state architecture, mentors junior engineers, and uses AI coding tools to accelerate development and delivery.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead technical design and architecture for analytics engineering: build and govern the semantic/metrics layer, optimize dbt and Snowflake for performance and AI use cases, mentor engineers, partner with Data Science and Engineering, drive data quality, CI/CD, observability, and deployment of third-party data and emerging tooling to support analytics, ML, and agent-based products.

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 and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

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.

Lead a team of analysts and data scientists embedded in sales to build rigorous pilot analyses, create executive-ready business cases, expand consultative analytics across the partner lifecycle, and publish industry insights while coaching and scaling the Solutions Analytics function.

The Senior Analytics Engineer will develop data pipelines, build models, and create dashboards to provide actionable insights for various teams. The role requires collaboration with multiple stakeholders to meet analytical needs and ensure data governance.

The Senior Reporting & Analytics Consultant leads customer-focused reporting and analytics engagements, developing solutions, supporting implementations, and training clients, while ensuring project success.

Perform cross-product credit analytics to inform underwriting, limits, and portfolio strategy. Build customer credit profiles, run experiments (A/B tests), uncover insights, recommend and execute policy changes, and communicate results to leadership. Leverage internal and external data, predictive techniques, and AI tools to optimize approvals, risk, and product performance while balancing growth and loss.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

Lead product analytics efforts to define KPIs, build measurement frameworks, analyze customer behavior, and generate insights that influence product and engineering decisions. Partner with Product, Engineering, and Data teams to design event tracking, run experiments, quantify opportunity sizes, and communicate recommendations through clear narratives and visualizations to drive product adoption, retention, and business outcomes.

Own end-to-end analytics modeling for a business domain: build and maintain dbt models and business marts on Snowflake, develop the BI semantic layer, define consistent metrics, create self-serve data products, and partner with Finance, Sales, Marketing, CS, and RevOps. Validate upstream data with the Data Platform team and translate ambiguous business questions into production-ready data models.

Design, build, and maintain Workday reports, dashboards, Adaptive Planning sheets, and automations. Deliver workforce analytics, forecasts, and visualizations to support workforce planning and data-driven HR decisions. Collaborate to develop scorecards and influence business outcomes with real-time and forecasted people data.

As the Director of Analytics, you'll lead analytics for MyPrize, optimizing performance across teams, developing reporting tools, and informing data infrastructure.

This role involves conducting advanced data analysis to drive strategic decisions, defining metrics, collaborating with teams, and improving performance through insights.