Aadithya Vidyasagar


  • I am a self-driven and proactive individual with a strong desire to thrive in an environment of growth and excellence. My goal is to build a rewarding career that fosters continuous learning and development while helping me achieve both personal and organizational objectives.
  • In 2018, I completed my undergraduate studies at NIT Nagpur. Following that, I worked as an Associate IT Consultant at ITC Infotech, where I gained valuable expertise in the investment banking domain. During this time, I had the opportunity to handle critical projects and engage directly with clients to meet their business requirements on an international scale.
  • After a successful tenure at ITC Infotech, I decided to transition into a more technical role and joined NetApp Inc as a Data Analyst. In this position, I honed my skills in building financial and customer usage reports using tools like SQL, Excel, and Tableau.
  • I completed my Master's in Business Analytics with a specialization in Data Science at the University of Texas at Dallas. My coursework includes diverse subjects such as Machine Learning, Predictive Analytics, and Programming for Data Science.
  • Currently I am volunteering as a Data Scientist with CrowdDoing, where I am contributing my skills to lead the development of a comprehensive data storage solution for the Catastrophic Wildfire Prevention initiative.
  • I am always enthusiastic about exploring and analyzing extensive datasets to derive valuable insights for businesses. I excel in aligning business strategies with established analytical approaches to achieve optimal operational impact with minimal resource utilization.
  • My expertise spans across data analytics, data engineering, cross-functional team leadership, and complex problem-solving. I approach each endeavor with a goal-oriented mindset, committed to delivering exceptional results.


Master of Science, Business Analystics

2021 - 2023
GPA: 3.918/4

University of Texas at Dallas, Richardson, TX

Relevant Courses : Database Foundations, Advanced Statistics for Data Science, Prescriptive Analytics, Programming for Data Science, Applied Machine Learning, Applied Econometrics and Time Series Analysis, Applied NLP, Predictive Analytics, Business Data Warehousing, Big Data and Business Analytics using R

Bachelor of Technology, Electrical and Electronics Engineering

2014 - 2018

Visvesvaraya National Institute of Technology, Nagpur, India


Python 100%
SQL 100%
Tableau 100%
Excel 100%
R Programming 70%
Snowflake 70%
Alteryx 90%
SAS 70%
Natural Language Processing 70%
Machine Learning 70%
Git/GitHub 100%
Project Management 100%

Professional Experience

Data Scientist

Aug 2023 - Present


  • Developed and maintained data pipelines using Azure Data Factory to ensure scalable, efficient, and reliable data storage, retrieval, and processing.
  • Led the development of a comprehensive data storage solution from inception to execution, involving gathering requirements, documenting needs, and creating a strategic plan.
  • Formulated a thorough strategic plan for the data storage project, taking into account scalability, efficiency, and the specific needs of the Catastrophic Wildfire Prevention initiative.
  • Implemented SQL for database design and management, ensuring efficient data retrieval and storage.
  • Oversaw a team of 15+ volunteers, efficiently assigning tasks and ensuring a 20 % increase in weekly task completion rates. Conducted and led 10+ weekly meetings, resulting in a 30 % improvement in team communication and collaboration.
  • Successfully coordinated and facilitated weekly meetings, utilizing tools such as Miro Board for collaborative planning and visualization.

Big Data Analyst

Oct 2020 - Jun 2021

NetApp Inc

  • Engineered and maintained robust ETL (Extract, Transform, Load) processes for revenue data using a combination of SQL and Azure Data Factory, optimizing data processing time by 40%.
  • Created revenue reporting dashboards using Excel and Tableau, effectively visualizing key performance indicators (KPIs) and providing real-time revenue analytics to stakeholders.
  • Utilized SQL queries and Excel functions to analyze revenue trends, resulting in a 25 % improvement in accuracy and efficiency of revenue calculations.
  • Collaborated with cross-functional teams to design and optimize SQL and Azure-based data processing and storage solutions, ensuring efficient retrieval of financial data, leading to a 20% improvement in database performance.
  • Streamlined the monthly revenue reporting process by developing standardized templates and workflows, reducing reporting time by 20% while improving the accuracy and accessibility of revenue data.
  • Presented revenue insights and performance metrics to stakeholders through clear and concise reports, enabling informed decision-making and supporting strategic planning initiatives.

Associate IT Consultant

Feb 2019 - Jun 2020

ITC Infotech India Limited

  • Conducted in-depth analysis of business processes and requirements within the investment banking domain, collaborating with stakeholders to gather and document business needs, resulting in improved overall efficiency.
  • Developed comprehensive business requirements documents (BRDs) and functional specifications, ensuring clear and concise communication between business users and technology teams for successful system development and implementation, with a 95% accuracy rate in translating business requirements into technical specifications.
  • Collaborated with data engineering teams to design and optimize SQL database structures, ensuring efficient storage and retrieval of financial data, resulting in a 20% improvement in database performance.
  • Conducted user acceptance testing (UAT) to validate system functionality and ensure alignment with business requirements, coordinating test scenarios and test execution, resulting in a 95% defect detection rate, successful system implementations, and a 20% reduction in post-production issues.
  • Documented test plans, test cases, and test results, ensuring comprehensive and up-to-date documentation for future reference and audit purposes.

Portfolio Projects

EV Station Location Recommendation

  • Researched, analyzed, and visualized California's charging station model using Tableau. Developed a Pythonbased machine learning model to predict the ideal number of charging stations. Integrated geospatial analysis to recommend optimal locations for an efficient EV charging station network.
Financial Markets Analytics

  • Conducted in-depth stock market data analysis, extracting OHLC data for various stock tickers/symbols and time frames. Utilized Snowflake Virtual Warehouse for efficient data storage. Used Python with TA-Lib for technical analysis and developed a custom function to identify ADX and PPO convergence and divergence patterns. Analyzed price behavior post-divergence, gaining valuable insights into potential trading opportunities.
Inflation & Price Time Series Data Analysis

  • Leveraged Alteryx to forecast inflation and prices across diverse industries in both pre and post-pandemic periods. Conducted comprehensive data collection and statistical analysis, employing time series techniques to gauge the pandemic's impact. The project's results shed light on industry-specific trends, offering crucial insights to aid informed decision-making for stakeholders.
Resume Selector

  • Using machine learning classification techniques, resume data was sampled, explored, cleaned, pre-processed, visualized using word clouds, segregated into training and test sets, and modeled with a Naive Bayes classifier. The resulting model achieved 80% accuracy on the test set, allowing for targeted resume selection.
Spam Detection

  • Performed data pre-processing, applied featurization techniques (Count Vectorizer, TF-IDF Vectorizer), and built a grid classifier model to classify the SMS spam dataset. Achieved high prediction test metrics of 0.94 F1-score.

  • Analyzed, organized, tested and delivered the ARAMCO IPO release by coordinating with several back-end and front-end teams to ensure a successful and smooth delivery well before the go-live date. I was commended by the clients and by my company for helping the organization achieve a massive milestone.
On-Premises to Cloud Database Migration

  • Designed end-to-end migration of on-premises SQL DB to Azure Cloud using Azure Data Factory. Seamlessly integrated on-premises data with Azure Data Lake for efficient movement. Utilized Databricks for end-to-end transformation from bronze to gold data containers. Implemented dynamic pipeline to track extraction, transformation, and loading. Integrated fully transformed data into Azure Synapse for advanced analytics
Cloud-Enabled Data Analytics for Store Sales Visualization

  • Orchestrated the creation of a robust cloud-based infrastructure on AWS, incorporating two S3 buckets for seamless input and output data management. Leveraged AWS Athena to efficiently process and transform raw store sales data into structured tables, optimizing queries for enhanced performance and responsiveness. Integrated Athena seamlessly with Tableau, producing compelling visualizations that provided stakeholders with valuable insights into US store sales trends across diverse industries and states.


These are a few recommendations from the people I have worked with such as my colleagues, mentors, friends, etc.



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