Sowmya Kuruba

510-***-**** # ad37x9@r.postjobfree.com ï linkedin.com/in/sowmya-kuruba § github.com/sowmyakuruba20 Education

San Jose State University Jan 2023 – Dec 2024

Master of Science in Data Analytics - GPA - 3.9 San Jose, CA Course work - Math and Statistics, Data Analytics, Big-Data analytics, Data Mining, Database, ML, DL Teaching/Research Assistant - Programming in Python, Math and Statistics, Database system Visvesvaraya Technological University June 2014 – June 2018 Bachelor of Engineering in Computer Science Bangalore, India Technical Skills

Languages: Python(Pandas, Numpy, Matplotlib, Seaborn, Scikit, Scipy), SQL, C/C++, Java Databases: SQL Server, Mysql, Postgre SQL, MongoDB, Neo4j ETL & Visualization: AWS Glue, Crawler, Tableau, PowerBI, Airflow, Quicksight Big Data Technologies: pySpark, MapReduce, Hadoop, AWS EMR, Redshift, Athena, Cloudfront, Cognito, Amplify Deeplearning: Keras Tensorflow, Pytorch

Machine Learning: Collaborative Filtering, A/B testing, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, GenAI Interpersonal: Leadership, Communication, Teamwork, Critical thinking, Problem-solving, Story Telling, Presentation Experience

Walmart Global Tech Sept 2021 – Oct 2022

Software Engineer III Bangalore, India

• Fabricated Data Warehouse and created ETL pipelines using AWS glue and AWS Crawler and optimized a long-running query performance on AWS Redshift, reducing costs by up to 75%

• Developed and Implemented personalized recommendation features using Java Spring Boot and Machine learning technologies resulting in the revenue by 19% and 20% growth in customer retention.

• Spearheaded the implementation of a Kubernetes-based CI/CD pipeline, resulting in a 40% decrease in deployment time and a 60% increase in overall system stability.

• Created and managed 10+ interactive data analytical dashboards with KPI reports using Tableau and Quicksight leading to a 45% improvement in data-driven decision-making and enhanced stakeholder insights. Accolite Digital LLC July 2018 – Sept 2021

Senior Data Analyst Bangalore, India

• Improved efficiency by optimizing a reverse engineering process using Snowflake querying, mem-caching, and Java-based custom data structure design, achieving a 70% reduction in processing time

• Utilized Power BI dashboards to drive data analytics efforts at EvalGround through extensive EDA, uncovering insights that reduced churn rate and expanded client base. These efforts led to a 20% surge in user engagement, a 15% uptick in completion rates, and a 25% enhancement in candidate performance, resulting in increased profitability. Projects

Ridership Prediction for Rapid Transit(BART) using Neo4j and ML Python, Neo4j, Cypher, SQL, ML

• Keynote Speaker at NODES2023 Conference, presenting on Improving Rapid Transit Utilization using Neo4j and Machine Learning (XGBoost)- Based Ridership Prediction for commuter-selected time periods to improve travel planning convenience — (Conference) (Github) (Medium) Yelp business analysis using Big Data Analytics AWS, EMR, Spark, Glue, Crawler, Python, NLP, QuickSight

• Empowered strategic decision-making by leveraging Yelp data with AWS services, showcasing expertise in cloud-based analytics using AWS Redshift, Athena, data transformation using AWS Glue, AWS Crwalers, EMR with Spark App, NLP and insightful dashboard creation with KPI reports on AWS QuickSight— (Github) (Medium) Recommendation system for Amazon products Python, ML, NLP, Collaborative filtering, Classification

• Developed an advanced e-commerce recommendation system catering to diverse user profiles through NLP, ensemble models, and hybrid collaborative filtering, statistical modeling optimizing user experience and personalization

— (Github) (Medium)

Chat with a Website/PDF Python, LLM, GPT-3.5, LangChain, RAG, Streamlit

• Implemented a chatbot enabling interactions with a website or uploaded PDF to gather information, leveraging LangChain, OpenAI, and Streamlit. — (Github)

Arrhythmia Heart disease Classification Python, Deep learning, time-series data processing, Classification Dec 2023

• Implementing a Deep Learning-driven arrhythmia heart disease classification on ECG data using CNN-LSTM-Transformer encoder Model — (Github) (Medium)