Konichiwaa!

I'm Akshay Jambekar


 

A Machine Learning Engineer

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Name: Akshay Jambekar

Job Role: Data Scientist

Experience: 3 Years 3 Months

Address: Pune, India

Skills

PYTHON 95%
Machine Learning 90%
SQL 85%
Data Visualization 85%
Statistical Analysis 70%

About

About Me

Data Scientist with a robust background of 3+ years as an Oracle Database Administrator, transitioning into data science with hands-on expertise in machine learning, deep learning, and data analysis. Proficient in developing predictive models, data visualization, and deploying deep learning solutions to drive business impact. Eager to leverage technical skills and analytical mindset to solve complex data problems and contribute to innovative solutions.

  • Profile: Data Science & Analytics
  • Education: Bachelor of Engineering
  • Language: English, Hindi,Marathi
  • BI Tools: Microsoft Power BI & Tableau
  • Other Skills: Cloud(Azure/AWS), Excel, Git, ServiceNow, Oracle DBA, Unix
  • Interest: Trading, Animes, Movies, Learning new Technologies

0 +   Projects completed

LinkedIn

Resume

Resume

I have over three years of experience as an Oracle Database Administrator and Data Science, specializing in database management, performance tuning, and data security. My passion for data has led me to transition into Machine Learning, where I've gained proficiency in Python, data analysis, and machine learning algorithms through various courses and projects. My strong foundation in database management provides a unique perspective on data handling and optimization, essential for building effective machine learning models. I am excited to apply my skills to deliver innovative solutions and contribute to cutting-edge projects in my new role as a Machine Learning Engineer.

Experience

 
June 2021-Present

Senior Software Analyst

Capgemini

1. Sales Prediction Using Linear Regression

Objective: Developed a predictive model to forecast sales for retail clients, optimizing inventory management and reducing stockouts.
Description:
Used historical sales data and various features like pricing, seasonality, and promotions to build a L2 Linear Regression model(Ridge).
Collaborated with the business team to deploy the model into production, resulting in a significant improvement in demand forecasting.
Tools: Python, Pandas, Scikit-learn
Outcome: Achieved an R² score of 0.85, enhancing inventory accuracy by 20%.


2. Sentiment Analysis of Customer Reviews Using NLP


Objective: Analyzed customer feedback to gain insights into product sentiment and drive marketing strategies.
Description:
Preprocessed text data from customer reviews, including tokenization, stop word removal, and lemmatization.
Utilized TF-IDF for feature extraction and trained a Random Forest classifier to predict sentiment.
Provided actionable insights to the marketing team, improving customer satisfaction.
Tools: Python, NLTK, Scikit-learn
Outcome: The model achieved an F1-score of 0.88, enhancing targeted marketing campaigns by 15%.

Jan 2021 – May 2021

Python Developer Intern

Leometric Technologies

Leometric Technology is an ISO 9001:2015 certified company that helps Startups, SMEs and Enterprises achieve their business goals by defining their mobile-based business initiatives and helping them gather benefits from the latest technologies in this space.

  • Developed backend APIs using Django, contributing to CRM and Society Management projects.

 

Education

 
Feb 2024 - Present

Professional Course: Data Science and AI

Boston Institute of Analytics.

Skills Acquired: Python, Machine Learning,Deep Learning, Power BI,SQL,Gen AI

2016-2020

Bachelor of Engineering

Dr. D.Y Patil College of Engineering,Ambi,Pune.

Grade: First class distinction.

Percentage: 77.12%

2014-2016

Higher Secondary School

Balaji College of Commerce and Science,Tathawade.

Grade: First class.

Percentage: 63.69%

Download CV

Projects

Projects

Below are the sample Data Science projects on Python, ML,DL,PoweBI.

Car-Purchasing-Prediction-ANN

Developed a model to predict the amount of car that can be purchased by a customer based on their Gender, Age, Annual Salary, Credit Card Debt, and Net Worth. The model focuses on estimating the purchasing power and providing tailored car purchase recommendations.

CIFAR10-using-CNN

Developed a CNN model to classify images from the CIFAR-10 dataset into 10 different categories, focusing on accurate image recognition.

Predicting-Academic-Risk-of-Students-in-Higher-Education

Developed a model to classify the academic risk of students in higher education, focusing on classifying students into categories: Graduate, Enrolled, and Dropout

Sales Forecast- Time Series Forecasting

Rohlik Group, a leading European e-grocery innovator, is revolutionising the food retail industry.We have used XGBoostRegressor for Time series analysis for predicting the number of orders (grocery deliveries) at selected warehouses for the next 60 days.

Spam Classifier

A spam classifier is a machine learning model designed to identify unsolicited and unwanted messages (spam) and distinguish them from legitimate messages (ham). By leveraging NLP techniques and the Naive Bayes algorithm, we can build an effective spam detection system.

Chatbot

ChatBot using NLP and Deep Learning for Personal Portfolio

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0 Projects
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More projects on Github

I love to solve business problems & uncover hidden data stories

 

GitHub

Contact

Contact Me

Below are the details to reach out to me!

Download Resume

Resume link

Contact Number

+ 91 7030250310

Email Address

akshayjambekar04@gmail.com

Address

Pune, India

 

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