Slava Kokaev

Architected and owned the Data & AI ecosystem powering ReturnPro’s SaaS platform, including the Data Hub (data lake + warehouse) and AiR — AI Intelligent Returns Engine. Designed the vision and architecture for agentic AI workflows, analytics, and BI reporting across internal and client-facing environments. Built core AI capabilities—including Catalog Enrichment, Price Optimization, Disposition Engine, and Customer 360 Analytics—improving automation, accuracy, and insight delivery. Directed the SaaS BI architecture and product strategy, delivering embedded Power BI experiences, governed data models, and multi-tenant self-service analytics. Defined and executed the AI and data strategy, driving automation, governance, and cloud scalability across the organization. Partnered with engineering, product, and leadership teams to align AI initiatives with ReturnPro’s commercial roadmap and client success goals.

Architected and led development of Azure-based data platform supporting trading, risk, and analytics operations for quants, traders, and executives. Built a unified data ecosystem combining Azure Data Lake, Databricks, and Snowflake, processing terabytes of market, transmission, and generation data daily. Developed ingestion and orchestration pipelines with Azure Data Factory, Logic Apps, and Functions, automating acquisition from diverse energy market systems. Designed ML enablement framework and data pipelines for quantitative modeling, powering predictive forecasting for congestion and transmission routes. Implemented DevOps, MLOps, and DataOps practices using Azure DevOps and Terraform, improving deployment speed and platform reliability. Delivered enterprise BI and analytics solutions in Power BI, enhancing speed, insight, and operational efficiency across trading and energy marketing. Led cross-functional team of 9 architects, engineers, and analysts across the U.S., India, and Mexico, ensuring consistent architecture and delivery standards.

Led cloud data architecture and infrastructure migration for major financial and asset management clients, enabling scalable, compliant, and cost-efficient data operations. Implemented enterprise data warehouse on Snowflake (AWS), delivering a single source of truth for portfolio management and financial analytics. Engineered near–real-time data pipelines using AWS Lambda, S3, Python, and Snowpipe, reducing data latency and improving analytical responsiveness. Deployed Infrastructure as Code (IaC) with Terraform and established CI/CD pipelines in GitLab, automating environment provisioning and code deployment. Collaborated with client architecture teams to design cloud governance, cost optimization, and DevOps best practices.

Microsoft P-TSP, Azure Ambassador. Architected an IoT analytics platform for a major healthcare provider, integrating data from 55K+ medical devices across 2,500 clinics. Designed an Azure IoT Hub + Edge architecture for real-time alerts, anomaly detection, and cloud analytics. Built a cloud-based Consumer Data Hub for a global retail brand, integrating POS, eCommerce, loyalty, and marketing data to deliver a 360° customer view and predictive insights. Developed data migration and modernization strategies to transition clients from legacy systems to Azure and AWS cloud platforms, improving agility and analytical scalability. Designed BI and self-service analytics frameworks using Power BI, enabling business teams to access governed, actionable insights. Collaborated with cross-functional stakeholders to define data governance, architecture standards, and scalable delivery practices.

Led the design and implementation of BI and analytics solutions for industrial cybersecurity and threat intelligence systems used by global energy and defense clients. Architected an analytical appliance (Security Analytical Manager) enabling real-time asset monitoring, change detection, and incident response. Developed and optimized data warehouses and multidimensional cubes (SSAS) for asset profiling, event tracking, and security KPI measurement. Built real-time ETL pipelines (SSIS) for ingestion and transformation of large-scale operational data, supporting near real-time analytics. Created interactive dashboards and reporting systems providing network intrusion visibility and system anomaly tracking. Collaborated with cybersecurity product and engineering teams to define data models, metrics, and visualization standards for intelligence operations.

Consulted across financial, healthcare, and media clients to modernize BI and data integration systems. Architected and optimized BI frameworks for Bain Capital, Microsoft Media, and Best Doctors, improving performance and analytical capability. Migrated and refactored ETL pipelines from legacy Pentaho to Microsoft SSIS, enhancing scalability and maintainability. Delivered high-impact analytics solutions using SSRS and SSAS, reducing reporting latency and supporting executive dashboards.