Ozone Park Apartments(T*/*A),

Sector – **, Faridabad, Haryana Soubhik Guha +91-880*******

admmb1@r.postjobfree.com

www.linkedin.com/in/sguha1997

SUMMARY

Self-driven and versatile data analyst with excellent problem-solving skills, and hands-on experience in business intelligence tools. Strongly motivated to implement and deliver projects with efficiency, accuracy and integrity. Proficient in communication and presentation skills. TECHNICAL SKILLS

Scripting/Libraries/D Python (3.7.8), Scikit-learn, Seaborn, Matplotlib, Pandas, MySQL (8.0)

Core Technology/Concepts Data Analysis, Data Visualization Machine Learning

Supervised Learning, Unsupervised Learning, Decision Trees, Linear Regression, Random Forests, Logistic Regression

Spreadsheet/Software Microsoft Excel, Tableau

EDUCATION

Post-Graduation Program, Data Science and Engineering July 2019 – Jan 2020 Great Lakes Institute of Management, Gurgaon, Haryana, India Coursework: Exploratory Data Analysis, Predictive Analysis, Statistical Analysis, Data Processing. Bachelor of Technology, Computer Science Engineering July 2016 –Jan 2020 ITM University, Gwalior, Madhya Pradesh, India

Coursework: Data Structures, Data Warehousing and Mining, Software Management, Distributed System. PROJECTS

Customer Lifetime Value evaluation for automobile insurance Objective was to find out the Customer Lifetime Value (CLV) for a US-based auto insurance company. CLV is a key metric that indicates the customer’s worth to a company. Key skills used were Data Cleaning and manipulation, Seaborn, Matplotlib, Scikit-learn, Linear Regression, Decision Tree, Random Forest.

Laptop Price Prediction

Objective was to discover laptop trends and demand across brands based on their types and performances. The project involved prediction of laptop prices based on aspects such as RAM space, storage size, CPU and GPU relative performances, screen size and brands.

Key skills used were Data Cleaning, Seaborn, Matplotlib, Scikit-learn, Linear Regression, Decision Tree. Car Price Prediction

Objective was to find out the price of cars with available independent variables, which was used by the management team to understand how exactly prices vary in accordance with the independent variables. Key skills used were Statistical observations, Seaborn, Matplotlib, Linear Regression, Decision Tree, Random Forest. Telemarketing call success prediction

Objective was to predict the success of telemarketing calls for long-term bank deposits. Dataset included direct marketing campaigns of a Portuguese banking institution, and the classification goal was to predict whether a client will subscribe to a term deposit.

Key skills used were Data Cleaning, Statistical Observation, Logistic Regression, Decision Trees, Random Forest. Alcoholic addiction assessment across USA breweries Objective was to determine US states with highest addiction to alcohol from a data set across 7000 breweries which included demographics details such as category, name, address, city, state etc. Key skills used were Pandas, Seaborn, Matplotlib, Linear Regression.