Who am I?

I’m Prabakaran Chandran , working as a Data Scientist with 4+ years of experience across different industry verticals. I have worked on interesting Data Science Problems for various fortune 500 firms.

Currently , I ‘m working in Captain Fresh as DS-II in the problem space of Aquaculture and Marine Resource Management.

I am experienced in building end to end analytics / data science pipelines ,developing Machine Learning solutions for traditional/CV/NLP problems and developing ML Micro-services and MLOPs lifecycles.

I have worked on 20+ Project Proposals and Solutions Designs during my work tenure in Mu Sigma and enabled teams to win million dollars worth of deals.

To Know more : https://www.linkedin.com/in/prabakaranchandrantheds/

Work Experience :

Lead Data Scientist, Mu Sigma Inc Jul 2022 – Nov 2022

  • Technically leading Supply Chain Transformation and Process Optimization Initiatives for a Saudi based Petrochemical
    firm worth USD 8M
  • Architected the Entire Supply Network Optimization and Demand Sensing Modules for the above-mentioned initiative
  • Developed Solutions for problem spaces such as Value-based pricing, Hyper personalization, and Customer 360
  • Presented State Of Art Machine learning solutions to leadership teams of various fortune 100 clients

Data Scientist, Mu Sigma Inc Jan 2019 – Jun 2022

  • Single-handedly created a custom-built ML Package to efficiently predict the solar energy output and bidding risk for
    a Japanese Green Energy Firm which had the potential savings of USD 6M
  • Built DIPP Pipelines range from small scale to High dimensional Meteorological data processing
  • Played a crucial role in developing Manufacturing quality assessment tools from data labeling to application deployment
  • Implemented Physics Informed Neural Networks for Manufacturing Process parameters configuration
  • Created Conditional Generative Adversarial Networks for 3D printing Design Validation
  • Created Agent-Based Modeling Roadmap for a US-based beverages client to understand the consumption behavior of
    the target population
  • Worked on Parallel POCs and experimented with emerging concepts such as Conformal Prediction, Causal Inference
  • Developed a Genetic Entity Recognition framework and trained pharmaceutical clients on adapting Natural Language
    Processing
  • Taken 20 Thursday Learning Hours within the org on interesting machine learning and deep learning concepts

As an Academic Contributor

  • Created 30 Hours worth of course Data Science with PySpark for a leading Indian Online Learning Platform
  • Mentored and Trained 25+ International Students on Foundations of Machine Learning and Analytics
  • Designed and Conducted 15 Hours worth of Analytics Boot Camp for an Engineering Institute

Projects (2019-Present) :

  • AI based end-to-end Potential Shrimp Supply Discoverability Engine
  • Computer Vision Based Additive Manufacturing Quality Assessment and Prediction
  • ML Based Solar Power Generation Prediction and Bidding Assistance for Intra Day Power Trade
  • Agent-Based Modeling of Consumer Behavior and Incidence Mapping
  • NLP-based Genetical Entity Recognition
  • Regression-Based Market Scenario Simulation
  • Discrete Event Simulation and Optimization of Retail Warehouses Operations
  • Geospatial Analysis of crowd behavior to assess the infrastructure requirements of a Smart City
  • Monthly Budget Estimation of Construction Projects
  • Price Elasticity Analysis and Insight Generation to enable the Value based dynamic pricing
  • RoBerta , Bert based NLP Models to classify tamil sangam era poems into various entities
  • Rshiny based Server Failure Profiling application to understand the Root Causes of IT Server Failures
  • Propensity Score Modeling and Multi Variate Matching to evaluate the performance of Promotional Campaigns