Senior Technical Lead @ Birlasoft | Data Scientist | Machine Learning | NLP | Predictive Analytics | Azure | Power BI | Cloud Data Engineering
Results-driven Data Scientist & Machine Learning Engineer with 10+ years of overall IT experience, bringing a strong foundation in Siebel CRM & DevOps automation into applied AI, Machine Learning, and Predictive Analytics.
- 🔭 Currently building demand forecasting, NLP, and optimization models at Birlasoft using Python, PySpark & Azure Databricks
- 🧠 Hands-on across the full ML lifecycle — EDA → Feature Engineering → Model Training & Evaluation → Deployment on Azure
- 📊 Proven record of building Power BI dashboards that drove a 20% performance improvement in business operations
- ⚙️ Unique edge: DevOps + MLOps — CI/CD, Docker, Kubernetes, Ansible integrated into ML pipelines for production-ready, scalable delivery
- 🎯 Mission: "Code with purpose, automate with intent, and innovate with data."
Languages & ML Frameworks
Cloud & Big Data
Data Visualization & BI
Databases & ETL
DevOps & MLOps
| Duration | Role | Organization | Location |
|---|---|---|---|
| Oct 2022 – Present | Senior Technical Lead — Data Science & ML | Birlasoft | India |
| Aug 2021 – Oct 2022 | Senior Siebel Administrator | Avisys Services | Manama, Bahrain |
| Nov 2019 – Aug 2021 | Siebel Consultant | Royal Cyber Inc. | Jeddah, Saudi Arabia |
| Jan 2018 – Oct 2019 | Siebel Administrator | IBM | Pune, India |
| Sep 2015 – Dec 2017 | Technical Support Executive | Tata Business Support Services | Pune, India |
Current role highlights (Birlasoft):
- Designed & deployed ML models for demand forecasting, NLP, and optimization using Python, Pandas, PySpark & Azure Databricks
- Delivered a 20% performance improvement through interactive Power BI dashboards
- Built scalable ETL pipelines in partnership with analytics, data engineering, and BI teams
- Applied predictive analytics to reduce delivery costs and improve delivery times
| Project | Description | Tech |
|---|---|---|
| 📊 Data Science Portfolio (TuteDude) | End-to-end Data Science pipeline — Python fundamentals → statistics → 12+ ML algorithms (regression, ensembles, clustering) → NLP → time series → capstone (heart disease prediction) → Streamlit deployment. 129+ notebooks, 64+ datasets. | Python, Pandas, NumPy, Scikit-learn, Statsmodels, Streamlit |
| ✍️ Daily Handwritten Notes | A daily-updated visual concept log covering Data Science & Statistics fundamentals — auto-indexed via a GitHub Actions workflow. | GitHub Actions, Python |
| 🐍 CodeBook — Pure Python Recommendation Engine | "People You May Know" & "Pages You Might Like" recommendation engines for a simulated social platform — built with zero external libraries (no Pandas/NumPy), pure dict/set algorithmic logic. |
Core Python, JSON, Algorithms |
- ✅ Microsoft Certified: Azure Data Scientist Associate
- ✅ Data Science Foundations Specialization
- ✅ Python for Everybody (University of Michigan)
- ✅ Introduction to Ansible: The Fundamentals
- ✅ Data Visualization using Microsoft Excel
- ✅ Building Your Leadership Skills
- ✅ PM Aspire Foundation — Project Management
🏅 Honors: STAR Winner — Individual Excellence Award · Customer's Choice — Customer Centricity
🔗 Full list & badges: Credly Profile
I'm always open to conversations around AI/ML, cloud data engineering, MLOps, and predictive analytics — whether that's collaborating, contributing to open-source, or exploring new opportunities.
"Code with purpose, automate with intent, and innovate with data."