Aditya Vikram Dandapat

• TensorFlow, Pytorch, Pandas - Implemented TensorFlow, Pytorch and Pandas modules for training models based on Images and end product from various online applications and platforms
• Teamwork - Collaborated with multi-disciplinary product development teams to identify performance improvement opportunities and integrate trained models
• AI Image Extraction - Incorporated Visual AI Images data to
  understand and translate complex business problems into machine
  learning problems
• Data modeling - Conducted data modeling, performance and integration testing
• Jupyter / Google Collab - Made use of Python, Jupyter notebook and Google Collab for programming implementation
• Benchmarking - Benchmarked end-to-end network performance on DSP and special-purpose accelerator platforms to pinpoint and resolve latency issues.
• Maintenance and Review - Reviewed code changes made by team for accuracy and relevance.
• Created customized applications to make critical predictions, automate reasoning and decisions and calculate optimization algorithms

• Implemented pre existing and latest updated algorithms
• Decision Making - Team decision making while increasing profitability by leveraging Data Science.
• Python, SQL server - Used Python, SQL server management, Gremlin (Azure Cosmos DB) for organizing and develop nodes for Knowledge Graph
• SQL server (Analysis) - Used Analysis modules to analyze resume data and organize large chunk of SQL data
• Flask API development and Integration - Developed several APIs
  regarding job, resume, location, etc and implemented pre existing and latest updated algorithms.
• Azure Devops - Worked on Azure Devops platform and made crucial pull requests on GIT.
• Data Extraction - Performed advanced data extraction and data
  manipulation
• BeatifulSoup Web Scraping - Implemented Web Scrapping using
  selenium, BeatifulSoup and Pandas
• Gremlin (Azure Cosmos DB) - Worked with Gremlin (Azure Cosmos
  DB) and identified, analyzed and interpreted trends in complex data sets using supervised and unsupervised learning techniques.
• Data Visualization - Conveyed data results using graphs and charts

• Data Analysis - Created and presented models for potential holdings to fund managers
• Machine learning integration - Created machine learning Tools that
  computed adjusted P/E values.
• Discover project - Worked for Discover project and applied Data
  visualization and data mining in order to process and scrape essential bank related data.
• Python, SQL - Used Python and SQL for manipulating data for proper data handling.
• Outlier Analysis - Identified data anomalies and worked with business units to perform root cause analysis and resolve issues.
• Teamwork / Collaboration - Worked alongside team members and
  leaders to identify analytical requirements and collect information to meet customer and project demands.
• Metric testing - Tested, validated and reformulated models to foster accurate prediction of outcomes.
• Flask API - Used Flask API and implemented various APIs related to
  bank data.
• Web scraping - Did Web scraping in Selenium and Pandas
  Converted various API modules usage from Java to Python as already trained and had experience as Java Full Stack Developer for almost 2 years

• Java Development - As a part of Discover Financial Services project, got experience in full-time Java Development along with maintenance and updating applications.
• Shell Script/ SQL - Made use of Shell Script and SQL Databases
  together alongside continuing with main process of debugging and
  deploying applications within given delivery period cycle
• Agile - Collaborated with cross-functional development team members to analyze potential system solutions based on evolving client requirements and followed Agile Life Cycle flow
• Spring Tool Suite - Configured and made use of various
  Auto-scheduled Jobs and Tasks and learnt process of Autosys and
  Spring Suite tool trade-off
• While maintaining good communication with client side and serving time as Team Lead, also helped in associating team with proper agenda and goals while giving daily updates in time and maintaining effective goal-delivery ratio

• Machine Learning - Implemented Artificial Intelligence and Machine
  Learning Algorithms - also Implemented Linear and Logistic Regression on several Financial Datasets.
• Prediction - Helped in making projections on future financial graph.
• Applied Categorization of various fields and Prediction of profit and loss using Logit Functions.
• KNN - Implemented KNN (K-Nearest Neighbour) Algorithms and various Neural Network modules using Octave.
• Got rating of 4.5 out of 5 from ML training department.
• CodeFLow - Created CodeFlow Analysis Diagrams to illustrate working of existing Machine Learning Algorithms used by OFSAA.

• Attended training courses in Android Programming and Core Java to build understanding of Android Application industry.
• Developed Android App on Euro Quiz using ANDEngine.
• Used Core Java in Android Suite and Android Studio 2.2.0 for basic app module mapping and also made use of Accelerometer, OpenGL 2.0, Texture Region, VertexBufferObjectManager for making array to list all vertices of texture to be drawn.
• Developed applications using Google Maps and used other sensors for make app more interactive.
• Developed Interactive Music Player on Android with basic features like categorizing favorites based on Albums, singer, genre, average time duration and date of song release.

Business And Management Database and Their Environment:
Database Design, Data Presentation, Data Anonymization (ADF) and
Data Modelling.
• 2:1 - Merit
• Completed professional development in Data Science

- Dissertation: Crime Prediction using Twitter Data - Data Mining
Approach

• Graduated with “First Class with Distinction”. Overall CGPA across eight semesters: 9.133/10.00.

• Scored the highest SGPA in the entire college in the final semester (10.00/10.00), and was among the top students in the first, second and seventh semester of college (avg of 9.40/10.00).

• Relevant Undergraduate Coursework: Programming OOP, Data Structures and Algorithms, Neural Networks, Artificial Intelligence and Expert Systems, Genetic Algorithms and Machine Learning, Probability and Queuing Theory (With Statistics), Discrete Mathematics, Algorithms.