Top Senior Data & Analytics Jobs in Wichita, KS

Investigate fraudulent accounts, payouts, traffic sources, and partner activity across rewarded mobile apps. Analyze fraud patterns and MMP data, build risk rules and verification controls, quantify financial impact, and report results. Partner with Product, Engineering, Growth, Support, and external partners to prevent fraud while minimizing false positives. The role also establishes review standards, mentors teammates, evaluates fraud tools, handles appeals, and helps develop AI-assisted fraud workflows.

Analyzes and processes large-scale assessment datasets, maintains psychometric software and statistical code, troubleshoots programs, develops quality controls, coordinates data transfers, supports standard-setting studies, and communicates results. The role also improves workflows, mentors colleagues, supports project planning, and collaborates with psychometricians and technical teams.

Build and maintain scalable, fault-tolerant data pipelines, warehouses, and analytics solutions. Transform complex structured and semi-structured data, automate delivery processes, improve data quality and reliability, and support enterprise data strategies. Collaborate with analysts, data scientists, actuaries, and business teams to translate requirements into solutions. Research new technologies, troubleshoot issues, maintain version-controlled code, and mentor data engineering team members.

Designs and maintains scalable data models, semantic layers, ETL/ELT workflows, data-quality frameworks, and governed analytics products for commercial operations. Owns data solutions from requirements through deployment, monitoring, documentation, and support. Partners with technical and business stakeholders to deliver trusted reporting, dashboards, scorecards, productivity measurements, and AI-enabled decision support.

As a Revenue Analytics Manager, you will own reporting for Sales, Marketing, and Customer Success, build dashboards, automate workflows, and ensure data quality.

Serves as the technical authority for Azure SQL architecture, deployment, security, performance, operations, and migrations supporting federal programs. Designs secure Azure Government database environments, leads on-premises SQL Server migrations, develops T-SQL and data models, builds Azure Data Factory pipelines, implements DevOps and infrastructure automation, troubleshoots incidents, optimizes costs, documents standards, and mentors team members. Collaborates with engineering, architecture, data, and DevOps teams on reliable data platforms.

Lead design and implementation of tracking with GTM, analyze user behavior in GA4, build BigQuery queries and dashboards, define KPIs with cross-functional teams, troubleshoot tagging/data issues, and perform deep-dive conversion and journey analyses to optimize web and mobile performance.

Owns executive reporting for autonomous vehicle system performance, including the weekly Software Performance Review and broader commercial readiness analyses. Synthesizes robotics data, diagnostic evaluations, and performance metrics into strategic narratives for senior leadership. The role aligns cross-functional engineering data, automates reporting pipelines and presentation generation, establishes visualization standards, and mentors junior engineers. It requires deep knowledge of robotics, autonomous vehicle performance, data architectures, executive communication, and AI-assisted development workflows.

Designs, develops, maintains, and optimizes complex data systems, SQL databases, ETL processes, data warehouses, reports, and .NET applications supporting pharmacy benefit management. Responsibilities include database performance tuning, troubleshooting pharmacy claims processes, developing scalable solutions, documenting technical designs, participating in Agile ceremonies, collaborating with stakeholders, mentoring teammates, and ensuring healthcare data compliance.

Performs audit-focused data extraction, analysis, and reporting using SQL, R, Python, SAS, Posit, and Snowflake. Supports internal and external audits, legal, compliance, and investigations by transforming complex datasets, identifying risks and trends, reviewing data models and process flows, and providing code feedback. Requires 5+ years of data analysis experience, a relevant bachelor’s degree, and strong querying and project management skills.