Data Science Machine Learning

Manasi Sarvankar

Boston, MA *****************@*****.*** +1-508-***-**** LinkedIn Profile

Summary

Data Science graduate with strong experience in cloud-native data engineering, distributed computing, and scalable ML pipelines. Skilled in deploying end-to-end AI solutions using Python, SQL, and AWS. Experienced with data infrastructure and visualization tools to support business growth and cloud optimization strategies. Skills

• Programming: Python, SQL, Java, R, C, MATLAB

• Data Science & Analytics: Data Preprocessing, Feature Engineering, Statistical Analysis, Predictive Modeling

• Machine Learning & AI: Scikit-learn, TensorFlow, PyTorch, Regression & Classification, Neural Networks, Large Language Models (LLMs), Prompt Engineering, Natural Language Processing (NLP)

• Big Data & Cloud Tools: AWS (S3, Athena, SageMaker, Comprehend), Google Cloud Platform, Hadoop, Hive, PySpark, Snowflake, DBT, ETL Development, VPC concepts

• Web & Backend Development: Node.js, Express.js, RESTful APIs, SQL Server Management Studio (SSMS), Middleware Architecture

• Data Visualization & BI Tools: D3.js, Tableau, AWS QuickSight, Matplotlib, Seaborn, Plotly

• Databases & Dev Tools: MySQL, Excel (VLOOKUP, Pivot Tables) Git, Agile/Scrum

• Cloud Networking (Academic Focus): Explored AWS VPC, load balancers, and IAM roles during deployment of coursework ML pipelines.

Education

University of Massachusetts Dartmouth

MS in Data Science (GPA: 3.9/4.0 )

May 2025

• Coursework: Machine Learning, Database Design, Big Data Analytics, Artificial Intelligence, Data Visualization, Mathematical Statistics, Advanced Data Mining, Business Intelligence D.J Sanghvi College of Engineering, Mumbai, India

Bachelor of Engineering - Biomedical Engineering

May 2023

• Coursework: Healthcare informatics, Hospital management, Database management, Fundamentals of data analytics, Deep learning, Big data, and cloud computing, Biomedical Instrumentation Projects

Capstone Project – Brainwave-Based Biometric Authentication

• Investigated EEG signals as a biometric modality using a dataset of 109 participants, aiming to classify legitimate users and intruders based on responses to cognitive tasks.

• Applied advanced signal processing techniques including Fast Fourier Transform (FFT), spectral entropy, coherence, mutual information, and wavelet transforms to extract meaningful and discriminative features.

• Trained and validated classification models (SVM, Decision Trees, AdaBoost) using Python and AWS-hosted Jupyter notebooks, achieving 63% accuracy.

• Documented full workflow logic and evaluation reports to support reproducibility and feedback-based iteration. Course Project – Global Country Insights (Data Visualization) Demo

• Designed and developed a web-based data visualization platform to enable comparison of countries across key indicators such as GDP, life expectancy, literacy rate, and healthcare access.

• Implemented the platform using HTML, CSS, JavaScript, and D3.js, building interactive maps and comparative charts with a responsive, user-friendly interface.

• Delivered a BI-style tool that supported exploratory data analysis for use by policymakers, researchers, and educators, enhancing accessibility to global development metrics. E-Commerce Platform (Database Systems) Link

• Built a backend-focused eCommerce platform using Node.js, Express.js, and MSSQL with SSMS, implemented REST APIs, product/cart modules, and SQL triggers for real-time sync.

• Designed and implemented a normalized backend schema with full CRUD functionality, triggers using SQL Server Management Studio (SSMS).

• Developed a responsive JavaScript frontend with search filters and seamless order workflows, enabling real-time user interaction with the backend.

• Presented the eCommerce project to database course students as a teaching assistant, upon faculty request, to demonstrate integration of middleware, database, and interface layers. Experience

Teaching Assistant – Machine Learning Coursework - University of Massachusetts Dartmouth

Jan 2025 – May 2025

• Supported grading and student queries for Machine Learning coursework, holding office hours and maintaining timely feedback cycles for over 40 students.

• Collaborated with faculty to clarify concepts and reinforce applied learning through discussions and real-world examples.

• Developed and presented a Twitter Sentiment Analysis project using XGBoost and Naive Bayes, used AWS Comprehend to compare model insights and showcase NLP techniques. Biomedical Engineer Intern - Jaslok Hospital & Research Center, Mumbai Jul 2022 – Aug 2022

• Collaborated with engineers and technicians to collect, process, and analyze performance data from medical equipment, including operating status, error logs, and usage frequency, to support preventive maintenance

• Maintained accurate records and equipment logs to ensure proper tracking of device status, maintenance schedules, and operational readiness.

• Contributed to team discussions by identifying recurring issues and trends in equipment behavior, helping propose data-informed improvements to streamline service response and equipment availability. Leadership Experience

President, Cyber Secure Computing Club Sep 2024 – Apr 2025

• Led the student cybersecurity club in planning and executing awareness initiatives and technical workshops on secure data handling and threat prevention.

• Organized and delivered sessions on digital risk mitigation tailored to data-driven environments, engaging students across technical disciplines.

• Grew club membership by over 60% and increased available resources by more than 15 through strategic event planning, outreach, and collaboration with university departments.

• Managed overall club operations, fostered cross-functional teamwork, and built a strong community around responsible data practices and cybersecurity literacy.

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