Working closely with stakeholders, product managers, and software engineers, while leading a team of data scientists and AI engineers to drive innovation and deliver impactful services, solutions and products.Responsible for designing, developing, and implementing advanced Generative AI solutions:I lead the design and development of GenAI solutions, utilizing Large Language Models (LLMs), multi-agent architectures, and Retrieval-Augmented Generation (RAG) to address complex business challenges. Leveraging models from ecosystems such as OpenAI, Google Gemini, Anthropic, and open-source frameworks, I work in fine-tuning models, prompt engineering, and flow engineering. Additionally, I build workflows with tools like LangGraph, Langsmith, and LangChain to deliver context-aware, real-time decision-making systems. My approach includes integrating hybrid AI architectures and composable AI designs to enhance adaptability and scalability for diverse teams.Demand Forecasting: Leading the development and operations of robust, scalable machine learning and statistical-based demand forecasting solution, capable of predicting demand for thousands of SKUs/Customer with precision across any temporal or spatial granularity. Delivers actionable insights to enhance decision-making and optimize business strategies.Marketing Mix Modeling (MMM): Developed a scalable hybrid MMM solution combining Bayesian and machine learning techniques, enabling marketing teams to optimize future budgets and gain profound insights into current strategies. Focused on enhancing decision-making and maximizing ROI through data-driven models.

Probabilistic Opportunity Scoring & Sales Forecasting: Developed a robust forecasting framework for a cloud computing management leader, utilizing probabilistic models and integrated with Tableau for advanced BI services.Spare Parts Sales Forecasting: Engineered a regression-based sales forecasting solution for a multinational food packaging and processing firm, spanning multiple geographies. Front-end BI custom-built using Flask.D2C Sales Forecasting Models: Designed predictive models for direct-to-consumer sales across various e-commerce clients in the USA and India, leveraging domain-specific data.Demand Forecasting: Implemented time series, regression, and deep learning models for supply chain, manufacturing, and e-commerce clients to enhance inventory management and demand accuracy.Long-Term Production Forecasting: Built plant-level production forecasting models using time series with Fourier harmonics for a US-based plastic manufacturing client; BI visualizations provided in Tableau.Media/Marketing Mix Modeling (MMM): Developed sophisticated MMM frameworks incorporating diminishing returns and ad-stock dynamics for budget optimization and statistical sales attribution for e-commerce and marketing agencies across the USA, UK, and India.Price Elasticity Modeling: Created regression-based price elasticity models for a leading US distributor of perishable goods to optimize pricing strategies and maximize demand and profits.Topic Modeling and Sentiment Analysis for marketing agencies helping in campaign optimisation, customer feedback, and brand perception. Business Intelligence and Data Automation: Designed wireframes and dashboards across various BI platforms, such as Tableau, and automated data engineering processes for multiple industries.Leadership in Data Science: Led a team of data scientists in developing, deploying, and managing diverse modeling frameworks, while spearheading research in machine learning and deep learning algorithms.

Delivering data science courses, lectures, and workshops to graduate, post-graduate students and working professionals. Subjects include: Data science fundamentals, Statistics, Programming with Python & R, Data Visualisation techniques, Machine learning foundation & advanced, Deep learning foundation, Basics of Tensorflow & Keras etc.

Electricity Load Forecasting Framework: Architected and maintained a high-resolution forecasting framework for the North Indian electricity grid with 15-minute temporal and state-level spatial granularity. Integrated Numerical Weather Prediction (NWP) methods as exogenous variables into statistical and machine learning models, incorporating an intra-day correction model for real-time error feedback and forecast adjustments.Renewable Energy Forecasting Models: Developed advanced short-term and long-term forecasting models for solar and wind energy using NWP and machine learning methodologies. Implemented intra-day correction algorithms to dynamically adjust to site-specific conditions and emerging trends.Data Engineering and System Design: Managed complex data I/O pipelines, including NC & GRIB file handling, data cleaning, transformation, and modeling. Designed and deployed an MVP architecture with robust database management, MLOps practices, automated orchestration of data scripts, API routing, and forecast data transmission to clients.Research and Development: Led initiatives in climate projection modeling, satellite-based nowcasting, and long-term meteorological forecasting.

PGP - Business Analytics, Business Intelligence & Data ScienceMajor Subjects:1. Statistical Methods for Decision Making2. Advance Statistics3. Data Mining4. Predictive Modelling5. Time Series Forecasting6. Machine Learning7. Optimisation Techniques8. Data Visualisation with Tableau9. Marketing & Retail Analytics10. Finance & Risk Analytics11. Web & Social Media Analytics12. Supply Chain and Logistics Analytics> Capstone / Thesis Project: Forecasting solar power for power plants using hybrid model of NWP (physics based model) & statistical / machine learning based model.Transcript - Https://olympus1.mygreatlearning.com/transcript/KTWPJZFV

Subject matter expert of E-tendering applications (ASP.net) developed for PSUs India.Client handling & interactions for system functioning to verify correct operations and detect errors.Represented clients for pre-bid meetings in their tender floating process from the application.Prepared evaluations of software and hardware and recommended improvements and upgrades. Conferred with staff, users and management to establish requirements for new systems or modifications.

Product & services SME for a multinational telecom company. Reporting, escalation and resolution of cases. Created checklists for review or inspection of completed projects. Investigated mechanical failures or unexpected maintenance problems.Published engineering reports to document design details or qualification test results.