Define and build the metrics framework for the digital ordering pipeline — from order intake through result delivery
Apply statistical methods for root cause analysis — diagnosing why systems fail, not just what failed
Partner with engineering teams to instrument data collection where gaps exist
Investigate ad-hoc data questions — diagnosing production issues, quantifying impact of incidents, and supporting root cause analysis
Document metric definitions, model logic, data sources, and dashboard design so the organization can maintain and extend your work independently

8+ years of experience in a data scientist, ML engineer, or advanced analytics role

- Solid foundation in statistics — hypothesis testing, regression, time series analysis, Bayesian methods




- Advanced SQL — comfortable writing complex queries across large, multi-source datasets
- Proficiency in Python or R for analysis, modeling, and automation
- Experience with ML/statistical libraries (scikit-learn, statsmodels, pandas, NumPy, or similar)
- Experience with AWS data and ML services (SageMaker, Redshift, Athena, Glue, QuickSight, or similar)
- Hands-on experience with Tableau
- Experience building anomaly detection or predictive models in a production or operational context
- Experience working across multiple teams or systems, synthesizing data from disparate sources into a unified view

📌 Senior Data Scientist AWS (Chandigarh)
🏢 Bebo Technologies
📍 Chandigarh