Data Science Machine Learning

Atharva Chundurwar

Tempe, AZ, USA ********************@*****.*** +1-480-***-**** LinkedIn

Professional Summary

Dynamic tech-savvy with an expertise in Data Analysis, Data Science, Business Analysis, Deep Learning and skilled in turning data into actionable insights. Achieved excellence in Data Science, Machine Learning and Coding competitions with a deep passion for solving real world challenges utilizing data.

EDUCATION

Master of Science in Computer Science Aug 2024 - May 2026 Arizona State University, United States (CGPA-3.89/4.0) Relevant Courses: NLP, Distributed Database Systems, Foundations of Machine Learning. Bachelor of Technology in Information Technology with Specialization in Data Science May 2020 - May 2024 Symbiosis Institute of Technology, Pune, India (CGPA-7.89/10) Relevant Courses - Data Structures and Algorithms, Data Science, Database Management, Machine Learning. Diploma in Business Management (DBM) Jan 2022 – Oct 2023 Symbiosis Institute of Business Management, Pune, India (CGPA-7.35/10) Relevant Courses – Economics, Finance, Accounting, HR. TECHNICAL SKILLS

• Programming Languages: Python, C, C++, SQL, R, PostgreSQL, HTML, CSS.

• Libraries: Keras, TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy, Spyder, Transformers, Hugging-face, Seaborn, Pyplot.

• Tools/Technologies: PySpark, MySQL, Tableau, AWS, Hadoop, Power BI, Git, Microsoft Office, MongoDB, JIRA.

• Skills: Data Science, Data Analytics, Business Analytics, Business Intelligence, Data Visualization, Data Engineering, Agile, Data Mining, Advanced Statistics, Database Management, Apache Hive, Apache Spark, Big Data Analytics. PROFESSIONAL EXPERIENCE

miniOrange Business Analyst Intern Jan 2024 - May 2024

• Conducted data analysis using Google Sheets and MS Excel, delivering over 15 actionable insights to team leads improving project efficiency by 10%.

• Formulated User Success Stories and gathered customer feedbacks to guide product improvements and introduced client incentive to increase customer satisfaction ratings by over 20%.

• Revamped operational strategy, clarified specific requirements for USA and Europe customers by engaging with over 10 clients resulting in 15% reduction in project scope changes. ACADEMIC PROJECTS

Manual Analysis of Reasoning Chains and Auto Evaluator using NLP, Python, Transformers, Deep Learning.

• Evaluated open-source and closed-source LLMs (Llama-3-8B-Instruct and Gemini-Pro 1.5 002) on SOTA logical reasoning tasks using LogiQA and ARCT datasets.

• Developed a robust error taxonomy to categorize reasoning chain failures into 5 broad and 9 subcategories.

• Built a custom GPT-based auto evaluator achieving 81.98% accuracy in classifying reasoning errors into broad categories

• Leveraged the use of technologies: Python, Hugging Face, Google Collab, Llama-3-8BInstruct and Gemini-Pro 1.5-00.2 Models. Quantitative Analysis of Dysrhythmia using DL and ML

• Implemented deep learning models and machine learning algorithms to predict dysrhythmia with 85% accuracy.

• Recommended model was adopted at Symbiosis Hospital, reducing diagnostic time by 20%, thereby optimizing patient care.

• Presented, published and authored a research paper at International IEEE Conference demonstrating model’s capabilities to over 100 attendees.

• Employed technologies: Python, Deep Learning Models: VGG16-CNN and Modified CNN, GoogLeNet-CNN, ML Models: Random Forest, Decision Tree, SVM.

Diabetes Prediction using Machine Learning and Deep Learning

• Developed a diabetes prediction model with 95.33% accuracy using Deep Learning Model (MLP) and compared it with Machine Learning Models.

• Maintained accuracy of medical status data, assisted medical practioners in making informed decisions, contributing to 10% improvement in diagnostic accuracy.

• Utilized technologies: MLP Classifier, ML Models: SVM, Random Forest, Decision Tree, Naive Bayes, XGBoost, Logistic Regression. Extracurricular Activities

• Volunteered at Moinee Foundation, teaching basic Mathematics, English, and Hindi to underprivileged children, improving their academic performance by 25%.

• Served as an Event Head and managed 4 University events attended by over 200 students.

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