Transform raw data into strategic competitive advantage — with predictive models, real-time BI dashboards, and AI-driven analytics that tell you what's going to happen, not just what already has.
Most organizations are sitting on enormous amounts of data but struggling to extract value from it. Yeskay's Data Science & Analytics practice bridges the gap between raw data and real decisions — building predictive models, automated pipelines, and executive dashboards that put the right insight in front of the right person at the right time.
We work with structured and unstructured data, across cloud and on-premise environments, using the tools best suited to your stack and your team's needs.
End-to-end data science — data engineering, modeling, visualization, and ongoing intelligence.
Churn prediction, demand forecasting, risk scoring, and propensity models built on your historical data — giving your teams a forward view, not just a rearview mirror.
Real-time executive dashboards and operational reports in Power BI, Tableau, Looker, or custom web interfaces — designed for the decisions your leaders actually make.
Robust ETL/ELT pipelines, data lakes, and warehouse architectures on AWS, Azure, or GCP — ensuring clean, reliable, and timely data flows to every system that needs it.
Statistical and ML-based anomaly detection for fraud, operational failures, quality control, and security events — alerting your team before problems escalate.
Segmentation, lifetime value modeling, next-best-action recommendations, and cohort analysis that powers personalized experiences and smarter marketing decisions.
Streaming analytics pipelines using Apache Kafka, Flink, and Spark Streaming — for use cases where decisions need to happen in milliseconds, not hours.
Across industries, our data science work translates directly into measurable business outcomes.
Accurate multi-horizon revenue and demand forecasts that improve planning accuracy and reduce inventory costs across sales and operations teams.
Identify at-risk customers weeks before they churn — with actionable intervention scores that let your retention team prioritize who to call first.
Patient risk stratification, readmission prediction, and population health dashboards that help clinical teams focus resources where they matter most.
Credit risk scoring, portfolio analytics, and market risk models that help financial institutions make faster, more confident lending and investment decisions.
Equipment failure prediction, production throughput optimization, and quality control analytics for manufacturing and logistics operations.
Multi-touch attribution models and campaign ROI analytics that reveal which channels and messages actually drive conversion — so you invest where it works.
Analytics and ML work that turned data into measurable business value.
Prophet + XGBoost ensemble across 40,000 SKUs — with promotional and external demand signals — giving buyers data-driven inventory recommendations and automated reorder alerts.
ML risk model integrated into EHR workflow — scoring every discharged patient and creating automated follow-up tasks for high-risk cases to reduce CMS penalties.
We match the technology to the problem — not the other way around.
A structured, transparent process that delivers value at every stage — not just at the end.
We assess your current data assets, quality, and gaps — then build a roadmap that prioritizes the analytics use cases with the highest business impact.
Clean, reliable data pipelines and a scalable warehouse or lake architecture that ensures your analytics are built on a solid foundation.
Iterative modeling with weekly demos. We validate against your business KPIs, not just statistical metrics.
Production dashboards, model APIs, and scheduled reporting pipelines — with documentation and training so your team can maintain and evolve the system.
Tell us about your data landscape and the decisions you're trying to improve. We'll design the right analytics architecture for you.