Shashwat Mohanta

AI/ML Engineer and Applied Data Scientist with nearly 8 years of experience architecting enterprise-scale Generative AI, Agentic AI, Machine Learning, and Marketing Analytics solutions across AdTech, MarTech, Automotive, Retail, and Digital Analytics domains, delivering intelligent, data-driven business outcomes. Proven expertise in designing and deploying production-grade multi-agent LLM platforms, AI agents, predictive pricing engines, MLOps pipelines, and scalable ML Microservices using Python, LangChain, Agno Framework, Kubeflow, Flyte, Docker, and GCP to accelerate AI adoption and operational excellence. Specialized in Large Language Models (LLMs), statistical modeling, time-series forecasting, Bayesian Optimization, Explainable AI (SHAP), Gradient Boosting (CatBoost, XGBoost, LightGBM), and Transformer architectures, enabling high-impact decision intelligence, campaign optimization, and predictive analytics at enterprise scale.

Recognized for driving AI platform engineering, cross-functional technical leadership, and end-to-end ML product delivery, integrating robust MLOps, model governance, and cloud-native architectures to build scalable, reliable, and business-centric AI solutions.

Founding Member – AI/ML at Growth Magic (2025-08 – Present)

• Agentic AI Platform Development: Architected a production-grade multi-agent LLM platform featuring intelligent orchestration, reusable AI skills, structured memory, and explainable report generation for marketing intelligence.
• AI Workflow Automation: Engineered 50+ reusable AI playbooks, an agent workflow builder, and an 8-agent Campaign Optimiser to automate cross-channel reporting, campaign diagnostics, budget pacing, and recommendation delivery.
• Creative Intelligence & Optimization: Developed an end-to-end Creative Intelligence platform leveraging LLMs, perceptual media deduplication, and agentic workflows to identify winning creatives, detect fatigue, and optimize campaign performance.
• Marketing Analytics & Decision Intelligence: Built AI-powered analytics agents integrating GA4, Google Ads, Meta, AppsFlyer, Adjust, and CRM platforms to automate data analysis, visualization, and executive-ready business reporting.
• AI Governance & Explainability: Established statistical validation frameworks, session-based asset management, and end-to-end audit trails to strengthen AI explainability, analytical transparency, and data governance.
• Successfully launched a multi-agent LLM system that reduced reporting time by 80%, enhancing operational efficiency and data accuracy.
• Developed a suite of analysis playbooks that improved query response quality and reduced the conversation iterations by 60%, enabling faster decision-making for marketing teams.
• Improved Meta and Google Ads campaign performance by an average of 10% ROAS through AI-driven recommendations generated by the Campaign Optimiser multi-agent framework.

Senior Data Scientist at Pixis (2024-02 – 2025-07)

• Enterprise ML Platform Engineering: Led the development of enterprise-scale MLOps pipelines using Kubeflow and Flyte, productionizing forecasting models for datasets exceeding 1M+ daily events.
• Model Deployment & Observability: Established CI/CD pipelines and model monitoring frameworks, enhancing deployment reliability, production stability, and SLA compliance.
• Optimization & Decision Intelligence: Integrated Bayesian Optimization into production ML pipelines, improving campaign ROI by 15% through intelligent bid and budget optimization.
• Scalable ML Architecture: Architected production-grade ML Microservices enabling real-time creative rotation and campaign optimization across digital advertising platforms.
• Technical Leadership & Engineering Excellence: Mentored Data Scientists while driving engineering best practices, scalable solution design, code quality, and production readiness.

Data Scientist II at Cars24 (2022-05 – 2024-02)

• Pricing Engine Development: Led the end-to-end development of the India Sell Online Pricing Engine, delivering scalable ML pipelines, pricing models, and production-ready APIs.
• Explainable AI & Pricing Transparency: Developed SHAP-based explainability models providing transparent vehicle pricing rationale through feature-level attribution.
• Predictive Pricing Optimization: Engineered a feedback-driven LightGBM pricing model, improving customer conversion by 7% through adaptive pricing optimization.
• Cost & Valuation Modeling: Developed CatBoost regression models to accurately estimate refurbishment costs and post-refurbishment vehicle appreciation.
• Demand-Supply Pricing Intelligence: Built an XGBoost depreciation model leveraging demand-supply dynamics, increasing pricing coverage by 5%.

Data Scientist Intern at Cars24 (2021-11 – 2022-04)

• Feature Engineering & Data Preparation: Engineered predictive features from 100+ vehicle inspection checkpoints to strengthen pricing model performance.
• Classification Model Development: Developed CatBoost classification models achieving 85% precision and 75% recall for high-value vehicle identification.
• Predictive Price Modeling: Built XGBoost pricing models delivering 87% prediction accuracy within ±10% pricing error.
• OCR-Based Data Engineering: Automated data extraction and validation from auction-house listings using OCR pipelines for machine learning datasets.
• Machine Learning Model Enablement: Supported end-to-end model development through feature engineering, data validation, experimentation, and model performance optimization.

Associate Projects at Cognizant Technology Solutions (2017-08 – 2020-11)

• Digital Analytics Transformation: Executed enterprise digital analytics initiatives across 15+ global brand websites by aligning measurement strategies with business objectives.
• Web Analytics Implementation: Implemented analytics tagging across 120+ e-commerce websites to enable customer behavior tracking, personalization, and remarketing.
• Business Intelligence & Reporting: Developed Adobe Analytics dashboards and performance reports delivering actionable insights across 100+ digital properties.
• Marketing Performance Analytics: Analyzed digital marketing performance using Google Analytics, improving Return on Marketing Investment (ROMI) by 15%.
• Cross-Functional Stakeholder Collaboration: Collaborated with business, marketing, and technology teams to deliver scalable analytics solutions and standardized reporting frameworks.

Post Graduate Diploma in Business Analytics – IIM Calcutta | ISI Kolkata | IIT Kharagpur (2020 – 2022)

Bachelor of Technology in Civil Engineering – IIT Guwahati (2013 – 2017)