Resume.

1. Siddhant Thakur
+91-8368103652 | siddhantthakur08@gmail.com
Summary
AspiringDataScientistwith1+years of experience inprojectworkandexpertise inMachine Learning,Statisticsand
Programming. InterestedinSportsAnalyticsandPredictionModelling.Currentlyexploringthe areaof Natural Language
Processing.
Skills:
 Programming: Python (2+ year, scikit-learn, matplotlib, pandas, NumPy), C (2+ years), C++ (2+ years), SQL (1+ years),
Java (1+ year), R (<1 year, ggplot2), Flask (<1 year), Flutter (<1 year), Dart (<1 year)
 Modeling: MachineLearning (Regression, Classification and Clustering: Linear Regression, Logistic Regression,
Decision Trees, Random Forest, K-Means Clustering, Neural Networks, etc.), Hypothesis Testing, A/B Testing, Natural
LanguageProcessing, Feature Selection (Forward Elimination, Backward Elimination, Pearson Correlation, Linear
Discriminant Analysis), Data Visualization
 Software and System: Android Studio, MacOS, Microsoft Office, RStudio, VS Code, Jupyter Notebook, Tableau
 Communicationand Presentation: Empathic listener, strong interpersonal and communications skills. Also enjoys
working as a team member as well as independently.
Languages: English, Hindi, German (Basic)
Education
SRM University, Chennai 06/2018-current
Bachelorof EngineeringinComputerScience- BigDataAnalytics|CGPA - 9.37
Apeejay School, Noida 04/2016-04/2018
Class12th
in Physics,ChemistryandMath withComputerScience |Percentage –90.8%
Experience
Gen-Y 08/2019- current
Data Science and ML team member
 Mentored students in a workshop, conducted by the team, over Linear Regression in Python.
 Expanded on Gradient Descent and Ordinary Least Squared in a related blog on Medium along with explaining the
basic concepts and the math behind it.
 Facilitated the team with the development of Exam Correction Automation project and wrote scripts for data
generation.
 Selected to attend and work with many GDEs at the GoogleExploreML Mentorship Bootcamp held on 19th & 20th
February in Google, Hyderabad.
Relevant Projects
National Football League (NFL) Game PredictionModel
 Built a model predicting the weekly game winners of the NFL using Random Forest Classifier in Python.
 Utilized statistics like Rushing yards per game, passing yards per game, sacks per game, etc. after applying Feature
Selection.
 Wrote ETL job to collect stats for the home and away teams for last 10 years using the python nflgame API.
 Predicted with an accuracy of 63.00% for the 2019 NFL regular season.
 Published weekly blogs on Medium summing up the winners and losers of that week.
SIH Internal Hackathon (Software) – SRM Institute of Science and Technology,Kattankulathur
 Competed against 40+ teams and got selected amongst the Top 5 teams to represent in SIH.
 Worked on medical data from different lab reports and created clustering models segmenting the patients in
different categories based on their parameters from those lab reports.
 Deployed the above-mentioned clustering models as an API using Flask framework.
NCAA March Madness2020 – OngoingProject
 Building prediction models for an ongoing KaggleCompetition focused on predicting the College BasketballBracket.