Top Data & Analytics Jobs in Cincinnati, OH

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Analyzes and interprets data from multiple sources, builds dashboards and reports, performs predictive analytics, and delivers insights for Sales, Marketing, and cross-functional decision-making. The role supports data governance, quality standards, data architecture, process improvements, business requirements intake, and stakeholder communication. It requires approximately two years of related experience and may mentor less experienced team members.

Own the architecture and hands-on development of Tala’s shared data and analytics platforms. Build semantic layers, governed business metrics, data models, pipelines, services, tooling, and AI-enabled analytics workflows. Lead cross-functional technical initiatives spanning Product, Engineering, Analytics, Finance, and Accounting; improve governance, reliability, usability, and documentation; resolve architectural bottlenecks; and mentor engineers through technical leadership.

Leads the commercial data ecosystem, including data integration, warehousing, governance, quality, stewardship, MDM, CRM, BI, and omnichannel systems. Partners with IT, commercial leadership, vendors, and stakeholders to establish trusted data sources and scalable infrastructure. Oversees AI, machine learning, predictive analytics, and responsible AI governance for commercial use cases. Ensures compliance with privacy, security, promotional, and healthcare requirements while supporting launch planning, field performance, training, and commercial decision-making.

Performs treasury finance operations, including loan sales, data analysis, reconciliation, and financial controls. Automates recurring workflows using SQL, Python, Excel, and AI tools; maintains and modernizes data pipelines; investigates discrepancies; and communicates insights to technical and business stakeholders. Serves as a subject matter expert on loan data and finance processes while supporting fraud prevention and financial governance.

Own and evolve the analytics platform, including data models, pipelines, metric definitions, semantic layers, dashboards, and self-service data products. Partner with cross-functional stakeholders to translate business needs into reliable technical solutions. Lead data initiatives, improve ELT reliability and governance, resolve quality issues, mentor teammates, and shape the Analytics team’s technical roadmap. The role requires strong SQL, dbt, modern data-stack experience, business communication, and independent execution in an ambiguous environment.

Supports reporting for ultra-high-net-worth clients by onboarding and maintaining portfolio data, generating performance and transaction reports, auditing trades and cash flows, resolving data discrepancies, and managing private equity and alternative investment information in Black Diamond. The role also assists with investment management and billing processes, maintains control procedures, and provides accurate, timely reporting to advisory teams.

Conduct market research and analysis on ADAS, autonomous driving, electronics, and automotive supply chains in North America. Develop forecasts, build industry relationships, identify technology trends, support sales and business development, present insights to stakeholders and clients, and contribute to industry reports and publications.

Collects, consolidates, cleans, analyzes, and visualizes experimental data from analytical equipment, test rigs, and pilot plants. Performs statistical analysis, anomaly detection, experimental design support, equipment validation, and QA/QC activities. Presents findings to technical leadership, identifies process improvements, and helps extract actionable insights from structured and spectral data.

Owns retention analytics for a new Loyalty & Retention organization, including churn definitions, survival analysis, forecasting, experimentation, acquisition attribution, satisfaction analysis, payment recovery, and save-desk performance. The role builds reporting and predictive models from scratch, partners with BI and actuarial teams, influences cross-functional decisions, and presents retention findings and forecasts to executives.