Tejas Nanaware [he/him]

I'm a

About Me

I am an experienced Data Scientist with a passion for Deep Learning. I like to solve real world problems with AI and have a proven research track record in Computer Vision and Natural Language Processing. Besides data science, I also like to watch anime and travel.


Discover a compilation of projects I've passionately developed during my leisure hours on this website.

Data Science & AI Research

I am a data scientist and AI researcher with 4 years of professional work experience and 3 years of academic research experience.

My journey in machine learning started with designing computer vision models for recognizing Indian Sign Language gestues on a live webcam video feed, implemented by using Haar Cascade Classifier. Having implemented this project at a school teaching Indian Sign Language in Mumbai, it felt rewarding and has been since motivated me to tackle real world problems using the power of AI. During my Masters Research, I took the challenge to design NLP model that would help people overcome Social Anxiety by suggesting sentences to talk about.

I love being up-to-date in the everchanging field of AI, by reading research papers about new algorithms and techniques. I try to implement the papers by applying the model architecture on a creative data to something unique.

Currently, I am applying my knowledge to solve problems in the healthcare industry tackling complex tasks involving health insurance claims, audits, and enable wide reach of medicines by promoting health insurance sales.

Projects

A collection of deep learning projects that I have created.

  • All
  • NLP
  • Vision
  • Generative AI
  • Classical ML
  • Visualizations

CUT-GAN for Coloring Manga

Color one piece manga using contrastive unpaired translation GAN

Sign Language Training Tool

Detected sign language gestures using webcam

StyleGAN for Generating Anime Faces

Generate anime faces with dcgan, stylegan and stylegan2

Towards Assisting Human-Human Conversations

Help people overcome social anxiety with GPT-2 suggested chats

Cat & Dog Classifier with Inception Blocks

Inception model for classifying cats and dogs

Top Gear Stig Introductions Generator

Design new ways to introduce the Top Gear UK character, Stig

Identify Real Disasters Tweets with BERT

Classify tweets about natural disasters whether they are real disasters or not using BERT vector embeddings

Identify Real Disasters Tweets with GLoVe

Classify tweets about natural disasters whether they are real disasters or not using GLoVe vector embeddings

Skil Cancer Detection with Multiple Inputs Model

Detect skil cancer using a neural network that accepts image and tabular data together

Native Language Identification using BERT

Identify native language of an author writing English novels

LSTM Chatbot

Created chatbots using LSTM to apply conversations using transformers architecture

Student Placement Guidance

Predict package a student would recieve upon completing undergraduate degree as a multi-class classification

Visualize Illicit Drug Abuse in Australia

Visualize illicit drug abuse in people of all ages in Australia

Predict Aviation Fatalities

Identify fatal accidents and predict the fatality of the aviation accident

Stock Prediction with SVM

Predict Bombay Stock Exchange stock prices using support vector machines

Work Experience

Professional Experience

Lead Data Scientist

April 2023 - Present

Cardinal Health, Chicago, IL

  • Led the development of Agentic AI powered semi-autonomous customer service agents, boosting productivity by 60% and increased customer satisfaction by 33% through personalized interactions
  • Defined and delivered the enterprise AI roadmap for multimodal email classification using LLMs and RAG with vector databases, reducing operational costs by 40% and increased customer service productivity by 20% across business units
  • Established enterprise-wide prompt engineering best practices and ethical AI governance for HIPAA-compliant applications; standards adopted across multiple divisions
  • Designed and optimized prompts for Multimodal Generative AI models, significantly enhancing auto-generated response quality and relevance, resulting in a 40% uplift in customer service agent productivity
  • Architected and deployed a 70B+ parameter LLM-based email generation platform, reducing average case handling time by 40% for 200+ agents, fully integrated into CRM workflows
  • Served as the Subject Matter Expert (SME) for Named Entity Recognition (NER) and extracted information using Document AI, Vision OCR. Designed NER models that achieved accuracy of over 94% while complying with HIPAA regulations
  • Implemented Retrieval Augmented Generation (RAG) to efficiently generate customer service email replies, significantly improving agent productivity. Created dedicated knowledge bases using PGVector for generating emails for 50+ categories
  • Conducted workshops and training sessions, to foster a data-driven culture within the organization. Mentored junior data scientists, and contributed to the team's skill development and a collaborative work environment

Data Scientist

August 2021 - April 2023

Healthcare.com, Chicago, IL

  • Designed Recommend Systems using Q-Learning Reinforcement Learning to optimize call buyer selection process and improve match rate by 11% uplifting revenue by $1.5 million per year
  • Increased sales conversion rates by 19% by deploying Multi-Critera Decision Making (MCDM) Ranking Systems for call centers through performance-based call routing
  • Researched & implemented Natural Language Understanding (NLU) Speech Recognition and Transcription using TensorFlow ASR and AWS Transcribe to understand speech characteristics for sales and customer intent of buying
  • Increased sales conversion rates by 8% using generative NLP Models, BERT, Transformers to produce sales scripts dynamically
  • Examined Clustering (Machine Learning) Techniques in Python to identify characteristics of top performing agents
  • Designed recruitment models that support in hiring top performing sales agents, successively adding $1.2M / year in revenue
  • Created Ensemble Learning Models using Gradient Boosting Machines (GBM) and Synthetic Data to verify customer lifetime value (LTV) and accurately determine customer duration for health insurance policies

Research Assistant

August 2020 - May 2021

Illinois Institute of Technology, Chicago, IL

  • Researched & designed Generative AI virtual chat assistants that support humans with social anxiety to communicate efficiently
  • Designed ensemble of open domain chatbots using GPT-2, Transformers and Encoders for context understanding and next sentence generation that helped to achieve fluent conversations
  • Deployed Large Language Models into production on AWS EC2 using Flask, NodeJS, Express and VueJS for real-time predictions
  • Improved Perplexity to 3.61 for testing data that was gathered while performing human study to achieve better conversations

Data Scientist

June 2018 - August 2019

S & S InfoTech Services Pvt. Ltd., Mumbai, India

  • Increased eCommerce sales by 12% by designing inventory management platform for demand forecasting using Prophet and ARIMA timeseries models
  • Applied K-means clustering for classifying inventory based on sales velocity and stock movement, enabling accurate reorder point planning and stock prioritization. Which lead to reducing overstocked items by 43%
  • Designed anomaly detection pipelines to monitor email spoofing attempts, reducing detection time from 2.2 hours to under 3 minutes and preventing an estimated INR 7.3M in potential fraud losses annually
  • Improved company outreach by 27% by developing context-aware chatbot using Google Cloud Platform and DialogFlow API

Machine Learning Research Assistant

June 2017 - June 2018

Indian Institute of Technology, Mumbai, India

  • Researched rapid object detection techniques for recognizing real-time video sign language gestures with Python and OpenCV
  • Deployed gesture recognition models on web application for practicing sign language gestures with PHP, Python and JavaScript
  • Identified key parameters that enhances the probability of students obtaining jobs at career fairs by analyzing student’s profile
  • Obtained principal components by applying dimensionality reduction like PCA and t-SNE using Sci-Kit Learn, NumPy and Pandas
  • Developed supervised and unsupervised ensemble learning strategies to predict pay range based on the candidate’s profile

Leadership Experience

Lead Data Scientist

April 2023 - Present

Cardinal Health, Chicago, IL

  • Founded and led the company's AI CodeJam Hackathon program for 2 years, resulting in 5 production-ready prototypes, including an LLM-powered case summarizer adopted business wide
  • Established Prompt Engineering Guidelines and Ethical AI Governance Framework for HIPAA-compliant GenAI use; adopted across multiple business units
  • Fostered cross-functional collaboration between engineering, operations, and analytics teams to accelerate AI adoption as a part of the AI Center of Excellence
  • Upskilled 10+ data scientists via workshops on RAG, multimodal AI, and LLM fine-tuning
  • Defined enterprise AI vision and aligned GenAI roadmap with cross-department OKRs, ensuring measurable ROI on AI initiatives

Data Scientist

August 2021 - April 2023

Healthcare.com, Chicago, IL

  • Created the organization's first AI adoption framework, enabling ML-driven lead routing, customer retention modeling, and sales optimization
  • Advocated for and implemented a centralized data quality and governance process, improving ML model reliability and adoption rates
  • Mentored 6+ junior analysts and engineers, transitioning them into applied data science roles
  • Introduced early NLP and text classification models for sales script generation, laying the foundation for later GenAI adoption

Educational Qualification

Master of Science & Computer Science

Illinois Institute of Technology, Chicago, IL

Thesis, Machine Learning, Natural Language Processing, Deep Learning, Combinatorial Optimization, Game Theory, Cloud Computing

Bachelor of Engineering & Computer Engineering

University of Mumbai, Mumbai, India

Artificial Intelligence, Human Machine Interaction, Distributed Databases, Analysis of Algorithms, Software Systems Architecture

Publications

Towards Assisting Human-Human Conversations

Diss. Illinois Institute of Technology, 2021 Thesis

DMARCBox - Corporate Email Security and Analytics using DMARC

5th International Conference for Convergence in Technology (I2CT). IEEE, 2019

FingerSpelling - Indian Sign Language Training Tool

18th International Conference on Advanced Learning Technologies (ICALT). IEEE, 2018

Exploratory Data Analysis using Dimension Reduction

IOSR J Eng (IOSRJEN) Best Paper Award

Improving Predictions Using Qualitative Parameters

JournalNX 3.08: 77-82

Recommendations

Stephen Perkins

Stephen Perkins

Principal Data Scientist

I had the privilege of working alongside Tejas for over a year and I was consistently impressed by his dedication, hard work, and technical expertise. During our time together, Tejas made a significant impact at Healthcare.com by implementing and leading the development of an agent ranking system that improved our sales processes and lead conversion. His passion for innovation was evident in the creation of the call matchmaker recommendation engine, which used a Bayesian approach to match customers with the right buyers. This resulted in more efficient call routing and a better customer experience. In addition, Tejas was instrumental in identifying areas for improvement, such as his discovery that one of our proprietary insurance products’ LTV assumptions were 4x higher than reality. He also drove the adoption of best practices, including utilizing mlflow, Kubernetes, and unit testing, which helped to ensure the reliability and scalability of our systems. Overall, Tejas was a valuable member of our team and I have no doubt that they will bring the same level of commitment and excellence to their next role. I highly recommend Tejas for any opportunity in the field of technology and data science.

Carlos Zelada

Carlos Zelada

Data Science Product Manager

I work with Tejas on several Data science projects. In the last project, we worked on a call routing algorithm where he increased a critical KPI. Tejas is a great data scientist with excellent technical knowledge. I was lucky to work with him, and he achieved great things. I'm sure he will add value to any company he is a part of. I can endorse him for his knowledge of AWS, python, MLflow, SQL, docker, lambda, and machine learning.

Kevin Park

Kevin Park

Vice President, Product

Tejas is a brilliant problem solver. During my time at Healthcare.com, I greatly appreciated how Tejas was able to apply various advanced statistical and machine learning frameworks when tackling a new business initiative and explain in clear detail the why's and how's behind his approach. Tejas is very technically adept and effective at trying new tools and platforms for model development, testing, and deployment. He is an all-around team player and a rockstar with immense operating capacity, and any data science function would be fortunate to have him. I personally would definitely work with him again.

Shlomo Argamon

Prof. Shlomo Argamon

Chair, Department of Computer Science

Tejas has great technical abilities and communication skills, but more importantly, has tremendous energy and initiative - a great drive to build, solve, and succeed. Unlike most master's students, who take on thesis projects supplied by their advisors, Tejas approached me with his own original idea, and a great plan for developing and testing it. In the course of working with him on his thesis, he was consistently creative and hard-working, and also took criticism and suggestions very well. He will be an excellent addition to any team where his skills enable him to contribute, and I expect him to grow towards leadership very quickly.

Pratik Deshpande

Pratik Deshpande

SDE Prime Video

Attention to detail, and diving in deep to understand and solve the problem is something I learnt from Tejas. I've worked alongside him during my bachelors and developed Machine Learning and Full Stack Development projects. Tossing ideas back and forth and quickly analyzing the problem and patiently formulating a plan to tackle it, makes Tejas stand out. We share our passion for Machine Learning, and he is always excited to share his knowledge with anyone and is willing to help people reach their full potential. I am glad to have gotten a chance to work with him, and learn from him.

Prashant Mahajan

Prashant Mahajan

Amazon Search Science & AI

We rarely come across real talents who stand out like Tejas. I had the pleasure of working with Tejas for four years of undergraduate at the University of Mumbai, collaborating on several projects. Tejas' ability to learn new concepts and technologies quickly and explain it in a clear and concise way made a dramatic increase in the productivity level of our team. I am amazed by his diverse skillset across various domains of Computer Science, Machine Learning as well as a keen interest in research work. Tejas' talent as a researcher and fluency across numerous tech stacks made him a valuable member of our team. I recommend Tejas and I am sure he will be an asset to the team.

Rutvik Bhende

Rutvik Bhende

Data Science & ML Ops

I have known Tejas for many years, and have worked closely with him in many AI-based projects. Tejas is passionate about many things, and he makes sure his acumen in each is increased continuously. He is a devout learner and sympathetic team player. He is skilled at working on multiple tasks concurrently, without compromising the quality of the results. I always look forward to working with him again, in the future.