Swapnil Tambe Email and Phone Number

Ontologie AI Pvt Ltd is a cutting-edge technology company specializing in a wide range of IT services. As a dynamic team of experienced data scientists, Python developers, Java experts, and full-stack developers, we are committed to delivering innovative solutions that empower businesses in today's digital landscape.Skills: Java · Android Development · Cascading Style Sheets (CSS) · React.js · Flutter · Deep Learning · Artificial Intelligence (AI) · Machine Learning · Amazon Web Services (AWS) · Python (Programming Language) · Flask

Project: GSP Retail Client (Grocery Sales Prediction) (Role: Data Analyst) at TechMahajan IT Solution, Pune (Oct-2021-Present)Tools & Technologies: Python, Pandas, Numpy, Sklearn, Matplotlib, Seaborn , ARIMA, Bitbucket, AWS, Docker• Developed a time series forecasting model to predict future sales for a grocery store using Python and the Prophet library.• Collected and cleaned sales data from the store's inventory management system and performed exploratory data analysis to identify patterns and trends.• Evaluated the model's performance using metrics such as mean absolute error and mean squared error and fine-tuned the model to improve its accuracy.• Deployed the model on AWS, created an API and set up a CI/CD pipeline for daily retraining the model.• Contributed to data protection, ensure that the model is deployed in a secure and compliant way.

Project: CCP for Co-op. Bank (Role: Data Analyst) at TechMahajan IT Solution, Pune (Oct-2020 to sep-2021 )Tools & Technologies: Python, Pandas, scikit-learn, XGBoost, Numpy, Matplotlib, Seaborn , Bitbucket, aws, Flask.Summary: • Developed a machine learning model to predict customer churn for a bank client using Python and the scikit-learn library.• Collected and cleaned customer data from the bank's database and performed exploratory data analysis to identify patterns and trends.• Used various classification algorithms such as Logistic Regression, Random Forest, XGBoost and selected the best one using cross-validation and evaluation metrics such as accuracy, precision and recall.• Deployed the model on AWS using SageMaker and created an API to serve the model to the bank's customer-facing systems.• Monitored and maintained the model's performance by retraining it on a regular basis with new data.

Project: Retail-SOA (Sales operation analysis) Role: Data AnalystDuration: Jan-2020 to sep-2020Tools & Technologies : MYSQL, PowerBI, BitbucketProject Summary: • Developed an interactive dashboard in Power BI for a retail company to analyze sales data, visualize trends, and identify key drivers of sales performance.• Connected to multiple data sources such as SQL databases and Excel files and performed data cleaning, preprocessing and feature engineering.• Created various visualizations such as line charts, bar charts, and heat maps to help the customer understand their sales data and make data-driven decisions.• Presented the insights and recommendations to the customer's management team and helped them identify opportunities for growth and optimization.