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

Hochschule für Technik und Wirtschaft Berlin

Applying NLP on Social Media datasets for Contextual Information Extraction and
Prediction Of Traffic Conditions
▪ Developed and innovative framework to extract and analyze real-time traffic-related
information from social media posts using advanced NLP techniques, aiming to
predict traffic conditions accurately
▪ Utilized state-of-the-art NLP method “Named Entity Recognition” for contextual
information extraction
▪ Applied different combinations of Machine Learning Models and Large Language
Models (LLMs), i.e. BERT and Bi-LSTM

Master Thesis

SICK Sensor Intelligence

Performed data analysis and modeling in process, factory, and logistic automation
environments to optimize operational efficiency and automation systems.
Applied uni- and multivariate time series analysis on sensor data with Python and
Azure to uncover trends, patterns, and anomalies, enabling predictive maintenance
and enhancing operational insights.
Executed practical implementations of statistical and machine learning techniques,
working in cross-system project teams to facilitate data-driven decision-making,
streamline processes, and foster innovation.
Python Programming, Data Science, Data Analytics, and Machine Learning
Big Data Technologies and Business Intelligence

Data Science - Intern

Institut für neue Energie-System (InEs)

Energy consumption segregation with Neural Networks.
Data cleaning and preparatory analysis.
Training and testing of Artificial Neural Networks.
Reporting of analysis results.
Collaboration with the customer.

Student Assistant in Machine Learning

Simba Infotech

As a frontend developer, developed customer's projects in various field and created requirement based interfaces while working in projects. Actively taken part in management of projects and hence gathered experience in project management as well.

Junior Developer

HN Techno

Developed an android application as a frontend developer for two universities of India, with a goal of digital exchange of knowledge through this application. Other than this, the application was also capable of digitalizing library functions and book keeping for physical resources of the clients.

Intern

As a recent Master's graduate in Project Management and Data Science from HTW Berlin, I bring a profound passion for leveraging data and computer science to address real-world challenges. My thesis project, which focused on extracting and analyzing traffic-related information from social media posts using advanced NLP and ML techniques such as Named Entity Recognition, BERT, and Bi-LSTM, stands as a testament to my capability to innovate and implement sophisticated data science methodologies.

Previously, I completed an internship at SICK Sensor Intelligence, where I performed data analysis and modeling in process, factory, and logistic automation environments to optimize operational efficiency and automation systems. I applied uni- and multivariate time series analysis on sensor data with Python and Azure, uncovering trends, patterns, and anomalies, enabling predictive maintenance and enhancing operational insights. I also executed practical implementations of statistical and machine learning techniques, working in cross-system project teams to facilitate data-driven decision-making, streamline processes, and foster innovation.

I have a strong background in data pipelines, machine learning algorithms, Azure Databricks, and other data analytics tools. Moreover, I am developing myself in cloud computing, as I believe it is a key skill for the future of data science. I aim to leverage my knowledge and skills to contribute to impactful and meaningful projects in the data science domain.

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The Battle

Joy Chatterjee

Preksha Bhavsar

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