M.Sc in Statistics with strong experience on Statistics, Predictive modeling, Machine Learning, Deep Learning, Time Series and AI. Expertise in domains Retail, Healthcare, Telecommunincations, Energy. Exposure into Insur…
M.Sc in Statistics with strong experience on Statistics, Predictive modeling, Machine Learning, Deep Learning, Time Series and AI. Expertise in domains Retail, Healthcare, Telecommunincations, Energy. Exposure into Insurance, Oil and Gas.
Independent Data science consultant and building the product for Retail (Beverages) product. Providing solutions using Data Science techniques and Forecasting methods.
Independent Data science consultant and building the product for Retail (Beverages) product
End to end product development using ML (XGBoost, LightGBM & Stack) and advanced Timeseries methods
Extraction of insights and identification of trend of a Product/Region level and recommend relevant techniques
Incorporation of hybrid models to optimize material inventory management
Co-ordination with team and deploy product using it in AWS cloud platform
Maintain the model updates using version control of Git-Hub
Tools/Software/Database: ML/AI, Git-Hub, VSCode (Python)Editor, Postman
Summary of agreement documents using Gen AI
Automation of large datasets into Summary reports using Python
Forecasting retail product in different with different market situations and external factors
Anomaly detection
Turbine failure prediction: Incorporation of fetched turbines sensors data(S3) with log analytics (Bedrock-NLP) and build comprehensive prediction of turbine failures for energy industry using ML and Gen AI
Tools/Software/Database: Advanced ML, AWS S3 and Bedrock, Hugging Face, Python
Document Analysis: Used LangChain with RAG to extract transactional details from vendor agreements
Transaction Extraction: Ensured accurate extraction of key terms from complex documents
Dataiku Pipeline: Built and managed data pipelines for efficient data processing and model development
Pipeline Support: Provided support and optimization for Dataiku project pipelines
Client Consultation: Delivered tailored solutions and insights for effective use of Dataiku
Tools/Software/Database: Gen-AI, Transformers, Hugging Face, Dataiku DSS and Python
Identified suspicious transactions in dental insurance
Managed the data engineering and data scientist team
Segmented customers and provided recommendations based on purchasing patterns
Utilized Data Bricks with Python, SQL, and R for data science projects
Integrated data with AWS S3 and developed ML models using AWS Sagemaker
Automated processes and deployed models using AWS Lambda and API Gateway
Monitored model performance and maintained version control
Created Tableau dashboards for product insights
Tools/Software/Database: Data bricks, Python, Dataiku DSS, Tableau, and AWS Sagemaker
Improve the collection of ready-mix concrete revenue from the vendors under construction area
Project maintenance and team handling
Tools/Software/Database: Python, Excel and Tableau
Data Pipelines: Built and managed pipelines on the DATAIKU platform, integrating various databases
ETL & ML: Implemented ETL processes, applied and refined ML algorithms, and maintained version control
Deployment: Developed end-to-end pipelines for data processing and deployed projects using Dataiku’s Bundle and Publish features
Tools/Software/Database: Dataiku DSS, AWS Redshift, Python and R
Data Integration: Integrated and extracted data from third-party sources for model development in Python
Visualization: Created visualizations with matplotlib, plotly, and Seaborn, and developed web apps with Dash
Forecasting & Reporting: Conducted healthcare forecasting and reporting using R-Shiny
Leadership & Mentorship: Led a team of 10 and provided guidance on statistical analysis, survey preparation, and technology upgrades
Tools/Software/Database: SQLite, Python, Visuals (matplotlib, plotly and seaborn, dash), R and CSV
Member of COE of D&A cluster to work on POC and IPs using open sources R and Python
Dental insurance identification of fraudulent claims extracting the insights using ggplot visualizations
Applied statistical analysis and machine learning techniques and solve over fitting issues
Sales Forecasting (Exponential smooth, Holt-winters and ARIMA) using time series
Tools/Software/Database: SQL, Python, Visual (ggplot), R, CSV and Excel
Worked under Analytics and Insights in the Retail and Telecommunication domain
Understanding data and extracting insights and hypothesis building
Identification most influential variables for the brand performance
Budget optimization for the brand better ROI using MMM
Improve the customer sales for the retail stores using MBA
Coverage Analysis on beverages (Coke), and P&G and Confectionery (Kraft foods-Dairy Milk) products
Customers churn analysis for a telecom company
Worked as a project manager and led 5 people of the team
Tools/Software/Database: SQL Server, SAS, R, Excel and Power Point
Mortality Analysis: Identified causes of IMR and MMR and analyzed ANC and chronic patients
Health Services: Deployed HMRI 104 vehicles to deliver essential health services to rural areas
Tools/Software/Database: SQL server and Excel
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