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