About Me

Sundeep Pothula

I’m a curious Data Scientist helping businesses to make data-driven decisions. I have more than 7 years of modeling, data mining experience and implemented machine learning models into production for Banks, Telecom, Insurance, and Chemical Industries. I specialized in Adaptive Real-Time Machine learning, feature engineering and created an open-source python library for scalable ML.

My Career

Product Data Science, Moveworks

Leading various data initiatives to improve the product roadmap for creating enterprise AI chatbot. Led projects to forecast user engagements and chatbot churn using the interactions data.

January. 2022 - Present, Toronto
Product Data Science, Moveworks

Director, Data Science, Cerebri AI

Led a team of Data Scientists and Sr. Data Scientists for designing and implementing the scalable predictive models. Headed projects with a major Telecom firm (100M+ customers) in the US and built models that predicted 70% of churn.

August. 2021 - December. 2021, Toronto
Director, Data Science, Cerebri AI

Principal Data Scientist, Cerebri AI

* Headed project with a global manufacturer client with 50M+ events and built models that identified >40% staff attrition. * Designed and implemented framework for lifetime value (LTV) models to measure customers' brand commitment and identify any upsell/cross-sell opportunities. Leveraged Next best action models to increase the LTV of customers * Led research and software teams, for building end to end Machine learning and data pipelines for the streaming data. * Developed and applied a patent for a Federated machine-learning platform leveraging engineered features based on statistical tests. US Patent No. 17/110022 – June 10, 2021

November. 2020 - August. 2021, Toronto
Principal Data Scientist, Cerebri AI

Mentor, Post Graduate Data Science program

Mentoring 30+ working professionals for the Post Graduate Data Science program by Great Learning, US-Canada. Conducting weekly sessions on Python foundations, Inferential statistics, and Machine learning using Industry case studies

Dec. 2020 - Dec. 2021, Toronto
Mentor, Post Graduate Data Science program

Senior. Data Scientist, Cerebri AI

Coleading company research efforts to develop new and improved data science solutions for fortune 500 Enterprises. Developed object-oriented pipelines for building and optimizing ML models to reduce the overall run time less than 50%

June. 2020 - October. 2020, Toronto
Senior. Data Scientist, Cerebri AI

Data Scientist, Cerebri AI

Developed and implemented a machine learning solution that predicted 75% of the customer churn for a telecom client. Designed use cases and built models for predicting Investment behavior of customers for an Insurance company in Canada. The model captured 70% of the customers investment behavior correctly in the top 10% of the model predictions.

Oct. 2019 - June 2020, Toronto
Data Scientist, Cerebri AI

Data Scientist (Intern), TD Bank

Worked with Enterprise Data Analytics team on a Phone channel analytics project for identifying root causes for different customer issues using Customer care call data which helped to reduce overall call volume by 2%. Also, worked with TD auto Insurance team for building uplift models to target TD auto insurance customers for improving the overall sales conversation rates and net revenues.

May 2019 - August 2019, Toronto
Data Scientist (Intern), TD Bank

Research Lead, Data Science lab

Lead a team of 10 Masters students for building ARTML open source library and worked on building Real Time Machine learning applications.

March 2019 - October 2019, Toronto
Research Lead, DSM lab, Rutgers University

MEng., Industrial Engineering (GPA 4.0)

Completed Master of Engineering in Industrial Engineering department (Data Science specialization) with 4.0 GPA. Worked on a Research Project Adaptive Real Time Machine Learning and created an open source python library for it.

Jan. 2018 - May 2019, Toronto
MEng, Industrial Engineering, UofT

Teaching Assistant, Data Science

Worked as TA for Big Data & Marketing Analysis, Statistical Data Analysis, Computer Programming, Introduction to IT consulting, E-Business Strategies and Linear ALgebra courses. Helped in Preparation of lab & lecture contents and graded the assignments.

Sept. 2018 - April 2019, Toronto
Teaching Assistant, University of Toronto

Research Student, Data Analysis - UHN

Assisted medical team for analyzing patient-centered research data to empower communities about Kidney transplantation. Responsible for Data processing, Data Exploration, building dashboards and presenting data Insights to the research teams.

Sept. 2018 - Jan. 2019, Toronto
Data Analyst, University Health Network, Toronto

Dy. Manager, GSFC

Worked as a Dy. Manager in an Hydrogen generation plant. Predicted Steam Reforming Catalyst life using Machine learning and optimized parameters to improve catalyst life by 10%. Key person responsible for the formation of Six Sigma cell in Organization and planned for six sigma project executions

July 2015 - Dec 2017, India
Dy. Manager, GSFC

BE(Hons.), Chemical Engineering,

Completed BE (Hons.) Chemical with 3.6 GPA. from BITS Pilani India.

Aug. 2011 - July 2015, India
Chemical Engineering, BITS Pilani

My Skills

My Projects

Adaptive Real Time Machine Learning (ARTML)

Developed an open source Python library (ARTML) for Real-Time Machine Learning Algorithms with better scalability performance.

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Loblaw Digital - Microsoft Hackathon, 2nd Prize

Developed application for detecting products in retail store shelfs using Microsoft custom Vision API. (Computer Vision)

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Pnuemonia Detection from Chest X-Rays

Developed scalable Deep Neuralnets (CNN + Linear models) for detecting Pnuemonia from Chest X-rays (Computer Vision)

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Predicting Customer Churn for a Telecom Industry

Built Online Machine Learning Models for predicting Customer churn. These dynamic models can update in real time with the new data.

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One Shot Learning for face detection (Computer Vision)

Developed photo face recognition system using One shot meta learning with TensorFlow

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Recommendation System

Built Collaborative filtering based recommendation system for User-Movies data

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ChatBot (Conversaional AI)

Built a contextual AI Chatbot that answers user specific queries about Indian Startups

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Search Engine Design (Information Retrieval)

Built and improved performance of a website search engine using Whoosh library in Python

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Natural Language Processing for Customer Reviews

Developed Text analysis tools for understanding User reviews (Key phrases identification & Sentiment analysis)

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ML for designing Data Science Course Curriculum

Developed a model that matches candidates Resume with best jobs from job portals using supervised algorithms and designed Data Science course curiculum using Machine Learning

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