Ayush Anand

I’m a data scientist with 2+ years of experience in ML, predictive analytics, SQL, Python, BI reporting, and data quality management. I specialize in translating business problems into data-driven solutions that teams can act on.

I’ve built and deployed classification, regression, clustering, forecasting (ARIMA/SARIMAX), and NLP models, with a strong focus on extracting reliable signals from large datasets. I also drive hypothesis testing, segmentation, churn, CLTV, and fraud detection to support measurable outcomes.

In my recent work, I’ve cleaned and validated datasets using ETL, preprocessing, and data governance practices, then delivered automated dashboards and reporting to improve client decision-making. I’m comfortable in Databricks-style workflows and I enjoy building repeatable analytics pipelines.

Across retail and operations analytics, I’ve used forecasting and customer-centric analysis to reduce wait times and improve procurement and waste management. Earlier at IBM, I built 10+ Power BI dashboards, improved reporting data accuracy by 20%+, and automated recurring Excel reporting workflows—saving 50+ hours annually.