Data Science Machine Learning

Rishikesh Kumar S

Bloomington, IN linkedin/rishikesh-kumar-s *******@**.*** +1-812-***-****

SUMMARY

M.S. Data Science candidate at Indiana University Bloomington with nearly 3 years of software development experience. Skilled in data pipelines, ML projects, ETL automation, statistical analysis, and data visualization. Passionate about applying data science to solve real-world problems.

EXPERIENCE

Wipro Technologies Chennai, India

Software Engineer Aug 2021 - May 2024

• Developed and maintained Data Hydration jobs within a Spring Boot application.

• Data Hydration is an elaborate procedure that involves moving data from one or more sources to a specific database, enforcing data quality regulations, and preserving data integrity within that target database.

• Automated data transformation processes through advanced SQL scripting, reducing manual intervention by 80% and i mproving data accuracy, which resulted in a more reliable dataset used for company-wide reporting.

• Implemented data pipelines with Apache Airflow and Apache Spark, optimized application performance with Hadoop.

• Examined the data for errors and inconsistencies, rectified or eliminated inaccurate and inconsistent data, and oversaw the archival and removal of outdated data from the active database when necessary.

• Conducted thorough code reviews by maintaining JUnit tests to identify and resolve bugs, ensuring the delivery of high- quality, error-free web solutions.

EDUCATION

PROJECTS

Prediction system for Bike Rental Demands in Metropolitan cities

• This project achieved accurate predictions to facilitate daily bike management using methods such as linear regression, random forest regressor, and decision tree regressor.

• Leveraging historical data and analyzing seasonal and environmental factors.

• It helps optimize bike availability and manage peak demand efficiently. Raspberry Pi-Based Leaf Damage Identification and Facial Recognition System using Machine Learning

• Development of a basic machine learning model that can identify damaged leaves and implement facial recognition through image processing using a Raspberry Pi.

• It can be applied in agriculture for plant health monitoring and security for access control. Sentiment Analysis on IMDb Movie Reviews Using Machine Learning and Deep Learning Approaches

• This project explores sentiment analysis on IMDb movie reviews using various machine learning and deep learning techniques.

• By leveraging a dataset of 50,000 movie reviews, the study implements feature extraction methods like TF-IDF, Word2Vec, and GloVe, alongside models such as Logistic Regression, Naive Bayes, Decision Tree, and BERT.

• Evaluated based on accuracy, precision, recall, F1-score. SKILLS

Technical Skills: PL/SQL, Python, Java, C, C++, Springboot, HTML, CSS, React.js, Oracle, R, Numpy, Pandas, Matplotlib, Scikitlearn, Junit, MySQL, MongoDB, PostgreSQL.

Developer Tools: Intellij, Oracle SQL Developer, Dbeaver, Ansible, Unreal Engine, Git, PowerBI, Android Studio, Postman, Shell Script, Agile Methodologies

Indiana University, Bloomington, Indiana, USA

MS. Data Science.

Courses: Algorithms & Analysis, Advanced Database concepts, Data Mining, Introduction to Statistics, Data Visualization

Rajalakshmi Engineering College, Chennai, India

B.E Computer Science and Engineering

Courses: Data Structures, Operating Systems, Artificial Intelligence, Software Engineering, Distributed Systems

Aug 2024 – May 2026

CGPA: 3.2 / 4.0

Aug 2017 - June 2021

CGPA: 8.21 / 10.0

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