Top Analytics Jobs in Dayton, OH

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.

Provide geospatial and market intelligence to support leasing, marketing, investments, and development. Maintain geospatial datasets and trade areas, perform location-based analyses integrating internal and third-party data, build maps/dashboards/reports, and apply AI-enabled tools and automation to improve research, reporting, and decision support across the organization.

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 Data Engineer will design, build, and support data environments, orchestrate pipelines, and implement data solutions for advanced analytics and machine learning, working closely with project teams.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Build, maintain, and validate production data pipelines and ETL infrastructure (BigQuery/GCS/dbt/Airflow alternatives). Ensure data observability, SLAs, and automated tests to deliver reliable datasets that support campaign decision-making and organizers. Collaborate with product and data teams across fast-paced, cycle-driven work.

Lead a small data engineering team partnering with Engagement Marketing to build scalable ETL/ELT pipelines, ensure data quality, define marketing metrics, integrate trusted data with ad platforms, and drive the data roadmap to enable measurement and growth.

Comerit seeks multiple consultants for data migration projects involving SAP and AWS technologies. Roles include Data Engineer and Architect positions focusing on Analytics and BI.

The BW/HANA Analytics Consultant will analyze HANA Calculation views, recommend performance improvements, and collaborate with clients on analytics transformation.

Lead an analytics implementation for Valvoline's Global Products segment, driving metrics standardization, reporting consistency, and data accessibility. Create a scalable data framework, improve decision-making through visual analytics, and coach internal teams on analytics best practices.

The role involves leading analytics implementation for Valvoline's Global Products, focusing on standardizing metrics, enhancing reporting, and building scalable analytics infrastructures using SAP Datawarehouse Cloud.

The Senior Analytics Consultant will enhance the BI platform's maturity, assist in governance, document KPI definitions, and facilitate data integration.

The role involves strategic business analysis, technical expertise in cloud platforms, data engineering, analytics, and project management to drive data initiatives.

Guide the evaluation and integration of SAP SuccessFactors and data analytics solutions, ensuring comprehensive insights and stakeholder collaboration.

The role involves leading the implementation of an analytics solution for Valvoline's Global Products business segment, focusing on standardization and visualization of metrics, data access, and analytics capabilities.

The role involves leading analytics solutions for Valvoline's Global Products segment, implementing a comprehensive data framework, and enabling insights through effective visualization and analytics practices.

Lead design and implementation of scalable data models and analytical tooling for Consumer Product. Partner cross-functionally to translate business needs into reliable SQL/Python data products, dashboards, and automated pipelines using engineering best practices (CI/CD, testing, version control, monitoring). Drive data-informed strategy and manage long-term infrastructure while supporting ad hoc requests.

Lead people analytics strategy and execution: build HR data governance, remediate UKG Pro data quality, deliver enterprise people scorecards and dashboards, advance analytics from descriptive to predictive, and partner with HR, Technology, and Finance to drive data-driven workforce decisions.

The Analytics Engineer will design and implement analytics solutions, maintain reporting dashboards, partner with Product on KPIs, and support marketing with analytics.

Lead the design and implementation of algorithmic trading strategies, oversee technical infrastructures, and mentor a multidisciplinary team while managing performance analysis and risk.

The Databricks Architect will design and implement large-scale data solutions, optimizing performance and reliability, while leading initiatives in data engineering.

Lead post-sales and revenue analytics by integrating product telemetry, support signals, and revenue data. Build scalable data models, reusable datasets, and semantic layers. Define SaaS metrics, forecast revenue and usage, predict expansion and churn, and deliver dashboards and insights to drive renewals, expansion, and revenue growth.

The Senior Analytics Engineering Manager will oversee analytics engineering vision, manage a team, ensure data quality, and drive data-driven decisions across departments.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.