About
Data Scientist with over 2 years of experience delivering end-to-end ML solutions. Proficient in Azure pipelines, AWS, Docker, Kubernetes, and MLflow, with expertise in machine learning models, NLP, LLMs, time-series analysis, and real-time fraud detection. Demonstrated success in reducing churn and enhancing operational efficiency through data-driven insights and interactive dashboards. Certified Azure Data Scientist dedicated to building scalable, high-impact solutions.
Work
Tata Consultancy Services
|Jr. Data Scientist
Highlights
Assisted in building transfer-learning machine learning classifiers with ensemble attention to score personalized customer offers; exposed real-time prediction using GraphQL API's, boosting campaign conversions 8% in A/B tests.
Streamlined SQL based ETL workflows with incremental loads and data-quality checks, reducing processing time by 20% and delivering customer-transaction data to Power BI dashboards for daily-decision making.
Tata Consultancy Services
|Data Scientist
Highlights
Architected a RAG-based, multi-agent customer-support chatbot using LangChain, prompt-engineering, and LoRA-fine-tuned LLMs on 200 K feedback records, boosted NPS by 12% and 15% faster resolution via A/B tests.
Engineered a real-time Azure fraud detection pipeline using an ensemble of Autoencoders for anomaly detection and LSTM for sequential analysis, cutting fraudulent transactions by 15% and transaction latency by 20%. Containerized microservices on Docker and tracked pipelines with MLflow for CI/CD.
Developed ARIMA and Prophet time-series features in Snowflake and SQL to extract seasonality and risk features by improving forecast reliability 5%, then trained LightGBM (churn) and XGBoost (loan default) gradient boosting models, saving $800k in revenue and reducing churn by 10%, risky approvals by 8%, and presented SHAP based insights in Power BI.
Partnered with data engineers to build PySpark EDA pipelines and a reusable feature store on Databricks, integrating Azure CI/CD with MLflow monitoring, accelerating analysis by 15%, cut model refresh cycles by 30% and maintained 99% uptime.
Education
North Carolina State University
Master's
Computer Science, Data Science
Grade: 3.5/4.0
GITAM University
Bachelor of Technology
Electronics and Communication Engineering
Grade: 3.6/4.0
Certificates
Microsoft Certified: Azure Data Scientist Associate
Microsoft Certified: Azure AI Fundamentals
Microsoft Certified: Azure Data Fundamentals
Microsoft Certified: Azure Fundamentals
Skills
Languages and Frameworks
Python, R, SQL, PySpark, SparkML, PyTorch, TensorFlow, Hadoop, LangChain, LlamaIndex.
Databases
SQL, NoSQL, MongoDB, Snowflake, Cassandra, Redis, Neo4J, VectorDB.
Machine Learning Techniques
Natural Language Processing (NLP), Regression, Classification, Clustering, Time-Series Analysis, Neural Networks, Transfer Learning, Computer Vision, Reinforcement Learning, Prompt Engineering.
Web and API Development
HTML/CSS, JavaScript, Django, Fast API, Flask.
Tools and Cloud Platforms
GitHub, Microsoft Azure (Synapse, ML Studio, Data Factory), Microsoft Fabric, Databricks, AWS (EC2, S3, EMR, EKS), Google Cloud Platform (GCP), Docker, Kubernetes, Tableau, Power BI, Apache Kafka, Airflow.