Madhav Kasare Email & Phone Number | - Data Scientist with total 9.5 years of experience in financial banking domain handling large scale data through agile methodology. - Proficient in Machine Learning - (Linear Regression, Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, Clustering, SVM, Time Series Forecasting),Data cleaning, preparation, Modeling, Validation and Visualization task. - Worked on complete project development lifecycle - 1) Extracting data from data sources (like Mainframes), Transforming it to suitable form and finally loading into target database table. 2) Business requirements gathering 3) Data preparation 4) Modeling 5) Model Validation 6) Visualization of result - Technical skils:- Python, AWS, Generative AI, LLM,SQL, SAS, R, Informatica(ETL), Teradata DB, Unix scripting, QlikSense and Advanced Excel.

Madhav Kasare

- Data Scientist with total 9.5 years of experience in financial banking domain handling large scale...
Pune, Maharashtra, India

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Madhav Kasare’s Phone Numbers +1 732-248-****

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Madhav Kasare’s Location Pune, Maharashtra, India

Madhav Kasare’s Current Industry Ltimindtree

Madhav Kasare’s Prior Industry Suryoday Small Finance Bank | Infosys | Jigsaw Academy

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Specialist - Data Sciences

2022-03-01 00:00:00 - Present

Deputy Manager - Data Science / Analytics

2019-10-01 00:00:00 - 2022-03-01 00:00:00

Technology Analyst, Data Analytics, Informatica (ETL), Teradata DB, SQL, Unix / Linux Scripting, VBA

2018-10-01 00:00:00 - 2019-10-01 00:00:00

Data Science Trainee

2018-10-01 00:00:00 - 2019-04-01 00:00:00

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Madhav Kasare is a - Data Scientist with total 9.5 years of experience in financial banking domain handling large scale data through agile methodology. - Proficient in Machine Learning - (Linear Regression, Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, Clustering, SVM, Time Series Forecasting),Data cleaning, preparation, Modeling, Validation and Visualization task. - Worked on complete project development lifecycle - 1) Extracting data from data sources (like Mainframes), Transforming it to suitable form and finally loading into target database table. 2) Business requirements gathering 3) Data preparation 4) Modeling 5) Model Validation 6) Visualization of result - Technical skils:- Python, AWS, Generative AI, LLM,SQL, SAS, R, Informatica(ETL), Teradata DB, Unix scripting, QlikSense and Advanced Excel.