Mohit Sharma
Senior Data Scientist
11+ years in IT & 7 years experience in Data Science, Advanced Analytics, Deep Learning & Machine Learning on Cloud and On- Prem across domains Telecom, Banking, Marketing, Supply Chain, Times Series Forecasting, Demand Forecasting, CPG Ecommerce etc.
Data Scientist-AL/ML
Machine Learning: Regression XGboost, RF, Naive Bayes etc
Deep Learning
MLops in Production
NLP-BERT etc
Statistical Modelling
Time series: ARIMA, SARIMAX
Power BI, Streamlit
Demand Forecasting
Python
CNN,RNN,LSTM,BiLSTM etc
GIT: Version Control
TensorFlow, Pytorch
Data Science / Advance Analytics/ Story Telling
Neural Network
WORK EXPERIENCE
Data Scientist
07/2022 - Present, Achievements/Tasks
Worked and execute the POC search relevancy: The creation of SOW and KPI metrics.
Designing the E2E solution for the use case on Azure and worked on data of Click Stream and Claim.
Different vertical of the POC inhouse developed: Descriptive & Predictive analysis of the above data and Conversation ratio of the search vs insurance claimed. Platform : Azure Notebook, Event hub.
Lead a team of 7 Data Scientist and cross-functioning within different teams.
Senior Technical Lead Data Science
09/2020 - 07/2022,
Achievements/Tasks
Deliver and develop the Machine Learning & Deep Learning and NLP solutions for inhouse and client. Hands on different projects: Time Series, Fraud and Anomaly Detection, Sentiment analysis, Multiclass classification. In the field of Supply Chain, Manufacturing, E-commerce. Lead team of 10 Data Scientist.
Multiclass Classification-Spare parts : Automated the manual process of classification of parts having 10k classes by developing model via Deep Learning. Improved KPI: Saved $2 million/month and Average handling time reduced by 50%. Algorithms: SVC, LGBM, Random Forest, MLP, Deep Learning (LSTM). Production: Azure Notebook, GIT versioning.
Anomaly & Trend Analytics: Processes millions of transaction data from Pricing and Logistic chain billing- LOBs. KPI: Saved $4 million/month and Average handling time reduced by 6%. Algorithms: Weighted Logistic Regression, Deep learning: MLP, Learning rate, Bi-LSTM, Hyperparameter tunningForest ,Mahalanobis-Distance, etc.
05/2019 - 06/2020,
Achievements/Tasks
Understanding the client business domains and Formulating business problem. Designing the analytical solution and production environment.
Sentiment Analysis and Topic modelling using BERT: Feedbacks via ILSA chat bot is stored in Snowflake-EDW. Used pyspark for extraction and applied NLP and Topic Modelling for sentiment analysis on users feedback. Algorithms: Distil Bert - Sentiment analysis, Bertopic - Topic modeling NLP: Drain Algorithm’s etc.
12/2015 - 03/2018,
Achievements/Tasks
Supply Chain Management: Predictive modelling for maintenance and optimization of inventory. Worked on data bricks and pyspark to extract data from EDW as Snowflake.
Improving and suctioning of inventory management by ABC, FSN & VED inventory metrics analysis. Bucketing of Inventory Management Algorithms: Statistical modeling, K-means.
07/2014 - 12/2015,
Achievements/Tasks
Support to the clients Generating monthly report. Coordinating with Application Team to support different applications used in the bank.
Experience in Budgeting, Cost Analysis, Forecasting, Client financial management, Revenue recognition, Project timeline / milestones.
05/2011 - 06/2014,
Achievements/Tasks
Coordinate the with different teams and support in IT related queries and dashboard making, clients calls interaction.
01/2009 - 03/2011,
Achievements/Tasks
Started working as IT infra engineer primary focus of end user IT infra support.
2004 - 2008,
MLOPS, Elastic Search, DL-Timeseries. Training: Algo- Expert-Coding and Large ML-Design (07/2021 - Present)
LANGUAGES
English
Native or Bilingual Proficiency
German-A1 Trannie
Elementary Proficiency
Wildlife Photography, Reading Books
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