Ajay Singh

Demand forecasting for FMCG pharma products using Multivariate time series methods for inventory management, supply chain management using forecasting and all other factors. Demand forecasting for more than 10k SKUs by using ML/DL/Statistical Modeling using multivariate and univariate modeling. Market Mix modeling for FMCG products to increase sales and distribution of add amount in various features, Using Bayesian modeling MMM, XGBoost, Catboost, Nbeats, etc. Shap values explainer using for ML, Statistical Modelling, hypothesis testing, Price Elasticity. Brand Image recognition by using Sentiment Analysis (NLP) on customer reviews.

Time Series modeling for future insurance claims using chain ladder and statistical methods. Reserve prediction modeling (prediction to repayment future claims). Creating Shiny-R APIs and dashboard for data analysis insights and forecasted values. NLP project for customer reviews and sentiment Analysis.

Demand forecasting (volume and revenue) using machine learning with python. SKU level forecasting for many countries, developed model and dashboard. Creating App for demand and revenue forecasting. Deployed app on Dellemc PCF cloud by Using yml file. Sentiment analysis of customers reviews (NLP) Classification modelling by using Keras. Release health prediction modeling (Software application predict to complete on time). Creating flask APIs for model deployment and data extraction from the Oracle database.

Big data insight generation in Retail data. Dashboard creation for insight results. Forecasting for retail product demand quantity for future months.

Campaign Data prediction: AI R&D project based on ANN and reinforcement learning. Sentiment Analysis: All social sites like twitter, Facebook, Instagram, etc comment classification in Positive negative and neutral relation to business. Developed AI part of Trackistic.com for auto assigning task, performance of user, and recommendations to user. All model implementation done by creating flask API in python. Time series forecasting by using ARIMA, XGBoost, Mix Model, holt-winter and LSTM in python (Keras) for hourly ad biding forecast. Deployment machine learning pipelines in server, update pipelines, monitoring performance of the deployed models.

Exome sequencing (NGS) Data analysis and visualization. Classification of the neoepitopes for the cancer with respect to immunity (using neural network (ANN) and machine learning methods). Clinical samples classification model on large scale data. Develop Statistical and machine learning pipelines for the analysis of NGS data. Analyse large-scale genomic data and develop statistical testing methods to support valid interpretation and inferences.

Fitting and analyzing primary and secondary data, providing graphs, interpretation, and summary of the results with best explanation. Waiting Average time related supply chain port unloading simulation project. Cost minimize logistic related project. Worked on Regression and multivariate models (Predictive models). Worked on MCMC simulation models (Policy review) and decision making (Simulation Techniques).