Joy Chatterjee

DCMN

Specialize in developing end-to-end ML infrastructures and solutions to tackle complex marketing challenges.

Work with and integrate advanced platforms such as Codeium, Cursor AI, ChatGPT, replicate.ai, fal.ai and many more to streamline research and accelerate development. Off and on designing scalable pipelines on native and cloud platforms, to activate real-time predictive models, time series forecasting, customer segmentation, ROI optimization and more.

Lead AI Engineer

- Led the project for multivariate time series forecasting of client campaigns, resulting in significant insights in ROI for TV campaigns.
- Implemented LLM-based chatbots for internal teams, using RAG architectures and context
tuning models.

Senior Data Scientist

The Joy of Data

Product Ops & Data Consultant, with over 10 years of experience in data science and three years in product led growth (PLG). Founder of The Joy of Data, based in Berlin.

For data, collaborative ventures with Mercedes, FedEx, Just Mad as well as AI startups such as brighter AI, DCMN focussing primarily into leveraging data for strategic product led growth.

For product, over the past three years, been a data partner for product teams. Responsible for boosting Product Led Growth (PLG) strategies through the application of data science methodologies and data analytics. Expertise domain includes proficiency in product operations, OKRs, KPI driver trees, cohort analysis, user segmentation and much more.

Founder

ShowHeroes Group

Data Scientist (In House Consulting)

brighter AI

Data Scientist

Data Engineer

Mercedes-Benz Research & Development North America, Inc.

Mavrx Inc.

Working on specific project oriented machine vision tasks to aid the system of smart farming techniques developed and monitored by Mavrx Inc.

Machine Learning Engineer

MARKABLE

Rochester Institute of Technology

Work at the lab mainly revolves around projects in the genre of algorithm development. The algorithms are aimed at solving various problems from the image processing and computer vision communities.

Graduate Research Assistant

Peer Advisor Leader

CESC Ltd.

Worked with a team of four to establish and implement control algorithms to modulate the outlet steam efficiency of the central boiler system in a thermal power plant.

Technical Intern

🌱 Founder, The Joy of Data 🎯 Helping Product Teams Grow With Data Science 🚀 Ex-Mercedes | Lead Data Scientist 🎙️ Speaker, Podcasts, YouTube

🚀 Lead AI Research Engineer | Data Science Expert | Product Coach 🚀

With over 11 years in Data Science and AI, I specialize in developing innovative, Data-Driven and AI solutions that elevate Product performance and drive Business Growth. I bring a unique blend of hands-on technical skills and strategic Product insight, supporting teams to leverage Data for informed decision-making and robust growth strategies.

🔹 Key Highlights:
	•	LLMs & Chatbots: Implemented advanced LLM-based chatbots with RAG architectures, boosting team efficiency and workflow.
	•	Predictive Analytics: Achieved a significant ROI increase on client TV campaigns through multivariate time series forecasting.
	•	MLOps & Automation: Created scalable pipelines with Docker & Kubernetes, ensuring seamless deployment and monitoring.
	•	Patented Innovations: Primary author on two patented ML technologies, focusing on object tracking and anonymization.
	•	Cross-functional Leadership: Successfully lead teams and mentor junior Data Scientists, ensuring collaborative, data-driven decision-making.

🔹 Technical Arsenal:
Python 🐍 | SQL 🗃️ | Big Data Ecosystems | Statistical Modelling 📊 | A/B Testing | Cloud Environments (AWS, Azure)

🎙️ Speaking Engagements :
An avid speaker at prestigious Data Science and AI conferences over the past two years, where he shares his insights and experiences to foster a collaborative and informed Data Science community.

Lead Data Scientist

MathWorks

Enabling the Team:
● Guide weekly discussions on Generative AI's business impact, driving insights and collaboration.
● Organize a hackathon to explore AI ideas, assess risks, and discover opportunities.
● Facilitate monthly knowledge-sharing sessions to share best practices and gather feedback across offices in different time zones (EMEA, APAC).
● Maintain a centralized knowledge base to streamline trainer workflows. Built scripts and automations to improve process efficiency and quality.

Individual Responsibilities:
● Perform needs analysis of skill gaps for teams of engineers and propose learning paths and training programs.
● Design and deliver content and training on data science, computer vision, image processing,  statistics, machine learning, and deep learning related topics.
● Capture post-training feedback from customers to improve product and training delivery.

Senior Training Engineer - Image Processing, Computer Vision, Machine Learning, and Deep Learning

Help engineers and scientists do their best work:
● Deliver courses on IP, CV, ML and DL 
● Work with customers to gather requirements and develop customized curricula 
●  Identify and implement delivery improvements based on student evaluations

Training Engineer - Image Processing, Computer Vision, Machine Learning, and Deep Learning

● Develop user-focused content explaining key concepts and solutions
● Collaborate with cross-functional team members
● Participate in the software design and development process
● Test and Validate capabilities of core MATLAB tools

Technical Content Developer

Advisors : Dr. Eli Saber, Dr. David Messinger, and Dr. Nathan Cahill 

I developed algorithms and conducted research  on the following main projects:
● Improving the Accuracy of an Object-Based Classification System  (Funded by 
   Department of Defense - DoD) - Segmentation and Classification
● Extracting Spatial-Information from Images (Funded by DoD) - Feature Detection
● Panoramic Image Stitching (Funded by Imaging Science Graduate Assistantship) - Computational Geometry

Please see "Projects" section for more details.

Relevant Coursework in Imaging Science
● Digital Imaging Mathematics
● Human Visual System
● Optics
● Fourier Methods in Imaging
● Digital Image Processing
● Radiometry
● Remote Sensing and Image Analysis
● Advanced Digital Image Processing
● Multi-View Geometry 
● Computational Methods in Imaging Science

Graduate Student

XEROX CORPORATION

R &D Summer Intern 
● Researched techniques for image stitching
● Developed MATLAB code to simulate images from multiple linear sensor arrays  
● Created algorithm to stitch images from  multiple low cost sensor arrays to enable wide width scanning

Multi-Sensor Image Stitching

R &D Summer Intern 
● Attended training for color device (printer, scanner) characterization and calibration techniques. 
● Researched different methods to reconstruct selective frequency components from spectrum data.
● Implemented edge detection (canny, scale space search) to automatically extract page profiles from reflective density sensor data.
● Stream lined the code  for learning periodic print defect (banding) and correcting it via electronic compensation techniques. 
● Assisted team in analyzing and logging results from a sixteen day experiment (four factor, two level, multiple responses)
● Attended on-site class for color device (printer, scanner) characterization and calibration techniques.

Image Quality and Consistency

R&D Summer Intern 
● Studied the use of centroiding algorithms to perform feature detection within an image.
● Developed image registration algorithms to enable the comparison of images captured at different stages in the printing process.
● Designed a graphic user interface using MATLAB to facilitate the processing of multiple images.
● Analyzed images to measure the amount of rotation & translation introduced by the paper path into the sensed image.

Sensor Modeling and Image Registration

MAGNA POWERTRAIN INC

NVH Engineering Intern
● Processed signals using DSP techniques (FFT) to identify the sources of noise and vibration in parts. 
● Researched Zwicker’s Loudness Model to quantify pleasantness of noise to the human ears.  
● Learned to setup a Data Acquisition System for Noise and Vibration Analysis. 
● Programmed in VBA to automate the data acquisition which improved efficiency  of the process from 10 hrs to 45 minutes.

Noise Vibration and Harshness Testing

Kirtas Inc.

R&D Engineering Co-op
● Learned basics of Digital Image Processing, Optics and Photography. 
● Detected the non-uniformity of brightness in the images.  
● Performed a mathematical analysis on the non-uniformity issue.
● Worked on and learned to operate BookScanAPT1200 (Book Digitizer).

Image Non-Uniformity Characterization

I help improve team readiness and innovation through hackathons, knowledge-sharing sessions, and process automation. I’ve designed and delivered training on Data Science, Machine Learning, and Deep Learning and co-founded public speaking programs at RIT and deliver training for MathWorks.

My focus is on making technical concepts accessible and creating practical learning content for diverse audiences.

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Joy Chatterjee

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