About
As a data science professional with more than 6 years of experience, I have developed a strong foundation in leveraging data to drive business insights and optimize decision-making. Throughout my career, I have honed my skills in data analysis, statistical modeling, ML and Deep Learning to extract valuable insights from complex data sets.
I have a proven track record of delivering successful projects, from ideation to implementation, in industries such as Healthcare, FMCG, IT, Manufacturing and Energy. My expertise lies in using Python, R, SQL, and other data science tools to extract meaningful insights and build predictive models that enable businesses to make informed decisions.
In addition to my technical skills, I am a strong communicator with the ability to translate complex data insights into actionable recommendations for stakeholders at all levels. I thrive in collaborative environments and enjoy working in cross-functional teams to solve complex problems.
I am committed to continuous learning and staying up-to-date with the latest trends and techniques in the data science field. As a passionate data scientist, I am always looking for new challenges and opportunities to apply my skills and make a positive impact on the organizations I work with.
For contacting, e-mail me at sharanagatac@gmail.comsee more
Experience
Tell us about your professional experience
Education
Where did you complete your basic education from?
Accomplishments
Certifications
LangChain for LLM Application Development
Issued : Jan 2024
Building Systems with ChatGPT API
Issued : Dec 2023
ChatGPT Prompt Engineering for Developers
Issued : Dec 2023
LangChain Chat with Your Data
Issued : Dec 2023
Projects
Demand Sales Forecasting of a Beverage product
Completion Date : Jun 2023
The aim was to forecast the sales demand of a particular beverage product for different regions in India for the upcoming year. External data provided were weather data, holiday data and distributor data with the help of which the forecasting was done. The model used was FBProphet.
Usage Forecasting of a Marketing Product
Completion Date : Aug 2022
The usage of a marketing product of a software company, used by different customers was forecasted for the next 6 months. This helped the company to capture the usage of the customers and the churn of the customers. Weekly data was collected for a period of 2 years for all the individual customers and the best of the three selected univariate models were used for forecasting. The overall accuracy was 88% across all the customers which made this project a huge success.
Bladder Leak Detection in Curing in Tyre Manufacturing
Completion Date : Feb 2022
Use classification models to detect Bladder Leak Cases in curing of the Tyre Manufacturing process. Tools used: Python.
Uniformity Scrap Reduction in Tyre Manufacturing
Completion Date : Dec 2021
Detect parameters which causes Uniformity Scrap in Tyre Manufacturing Industry and use a classification model to detect Uniformity Scrap. This reduced the Scrap generation to a huge extent. Tools used: Python
Smart Scrap Bin Scheduling System
Completion Date : Mar 2021
Forecasting the amount of waste generated by each department of steel plant using AutoARIMA and FBProphet, which will lead to a projected cost saving of INR 30M annually. Tool used: Python
Cobble(anomaly) Detection in Bar Mills
Completion Date : Mar 2020
Anomaly detection/Cobble detection for different stands in bar mill using clustering and Logistic Regression. This helps in raising alarms in unwanted cases which will, in turn, lead to an annual cost saving of INR 20M as well as ensuring safety for the field workers. Tool used: Rstudio, Python, SQL
End Point Temperature prediction of Steel in Steel Manufacturing
Completion Date : Jul 2019
Temperature Prediction in steel making process during a complex thermodynamic process using Gradient Boosting machines and deployment of the model on a live server, which will lead to a projected cost saving of INR 200M annually. Tool used: Rstudio
Predictive Maintenance of Waste Gas Fans in Sinter Plant
Completion Date : Jun 2019
Anomaly detection/Predictive maintenance for fans used as waste gas exhausts of the Sinter plants area using Multiple Linear Regression. This helps in raising alarms in unwanted cases which will, in turn, lead to an annual cost saving of INR 2M. Tool used: Python
Visualisation and Analysis of Accidents
Completion Date : Aug 2018
Analysis of accidents on the Chennai Highway between Tambaram and Tindivanam stretch.
Languages
Bengali
English
Hindi
About
As a data science professional with more than 6 years of experience, I have developed a strong foundation in leveraging data to drive business insights and optimize decision-making. Throughout my career, I have honed my skills in data analysis, statistical modeling, ML and Deep Learning to extract valuable insights from complex data sets.
I have a proven track record of delivering successful projects, from ideation to implementation, in industries such as Healthcare, FMCG, IT, Manufacturing and Energy. My expertise lies in using Python, R, SQL, and other data science tools to extract meaningful insights and build predictive models that enable businesses to make informed decisions.
In addition to my technical skills, I am a strong communicator with the ability to translate complex data insights into actionable recommendations for stakeholders at all levels. I thrive in collaborative environments and enjoy working in cross-functional teams to solve complex problems.
I am committed to continuous learning and staying up-to-date with the latest trends and techniques in the data science field. As a passionate data scientist, I am always looking for new challenges and opportunities to apply my skills and make a positive impact on the organizations I work with.
For contacting, e-mail me at sharanagatac@gmail.comsee more
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