Data Analyst Python

Aniket Kumar

linkedin.com/in/aniket-kumar** github.com/Aniketkumar18 806-***-**** ******.***@*****.*** TECHNICAL SKILLS

● Technologies: Python, Scikit-learn, PyTorch, Pandas, Numpy, Matplotlib, Seaborn, SQL, MySQL, Tableau, AWS

(SageMaker, Kineses, EMR, Lambda, S3, Athena, QuickSight), Spark, Fast.ai, Hadoop, Databricks, SAS-Viya

● Machine Learning: Supervised Learning (Linear/Logistic Regression, XGBoost, Random Forest), Unsupervised Learning (K-Means, Clustering), Deep Learning (CNN, RNN, LSTM, NLP), Feature Engineering (PCA, One-Hot Encoding, Vectorization, Normalization)

WORK EXPERIENCE

Cognizant Data Scientist Jul 2018 - May 2019

● Created customer segmentation based on demography, age, income, and revenue using K-Means Clustering implemented in Python and Jupyter Lab, increasing ROI from marketing by over 7%.

● Performed sentiment analysis on customer review data using NLP and LSTM in Python, PyTorch, and Jupyter Lab, improving customer satisfaction by 60%.

● Developed supervised and unsupervised Machine Learning models using Gradient Boosted Decision Trees and Principal Component Analysis to conduct anomaly detection and information filtering on large scale data (10+ million rows and over 200,000 customers) using Python and Scikit-learn.

● Evaluated model performance in both simulated and real-world environments using RMSE, Confusion Matrix, ROC, AUC, Cross Validation, and A/B testing using Python and Scikit-learn, increasing recall rates to 94%.

● Created data pipeline to feed machine learning models and transfer on-premise customer data to cloud using AWS DataSync, reducing storage costs by 23%.

Cognizant Data Analyst Jul 2015 - Jul 2018

● Identified outliers and inconsistencies in data by conducting exploratory data analysis utilizing Python and performing data visualization with Matplotlib to gain actionable insights and validate features.

● Collected, organized, and analyzed customer data from more than 200,000 customers using SQL and Python.

● Engineered dashboards and handled client calls using Tableau to provide insights from data and discuss next course of action in adopting new marketing strategies. Beaming India Solutions Data Analyst Sep 2014 - Jun 2015

● Re-engineered 13 different internal documentations related to technical customer support, saving 8 hours per week for support desk team in resolving tickets.

● Provided business solutions to automate client-side validation checks with Advanced Excel Macros (VB Scripts) which generated ~$20,000 in savings.

EDUCATION

Master of Science in Data Science, Texas Tech University May 2020 Bachelor of Engineering in Electronics and Telecommunications, Nagpur University Aug 2014 PROJECT WORK

Amazon Review Sentiment Analysis Data Scientist github Apr 2020 Performed sentiment analysis on Amazon customer review data to determine positive or negative text.

● Created embedding layer using Python and PyTorch to learn semantic representation of different words and perform dimensionality reduction of reviews to achieve ~200 character count length.

● Designed recurrent neural network (RNN) using LSTM and implemented in Python and PyTorch to achieve an accuracy of about 82%.

● Performed hyper parameter tuning using Python, PyTorch, and AWS SageMaker, improving model accuracy from 82% to 87%.

CERTIFICATION + AWARDS

AWS Machine Learning Specialty, Amazon Web Services Apr 2020 AWS Cloud Practitioner, Amazon Web Services Mar 2020

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