SMITHISH JOSE

We are an AI Research Company with the goal of popularize AI usage and benefits among organizations and businesses to take data-centric decisions on every decision-making events at the quickest means possible. As part of this goal, AiWhiz enables Organizations to take AI-Driven Decisions through AI platforms and products. Following are the cutting-edge AI assets AIWhiz could create. 1. Generative AI Powered Platform for Impact Analysis / Cause & Effect Identification 2. No-Code AutoML Platform (www.aiwhiz.co) for Predictive, Prescriptive and Forecasting Use Case Design 3. Data Analysis Framework 4. Smart AI Assistant Framework 5. AI-Detection Framework for plagiarism analysis & Content verification 6. FarmWhiz an AI Assistant Framework for agriculture optimization and Farmer’s education 7. MediWhiz (https://mediwhiz.aiwhiz.co) for symptoms to disease identification My key responsibilities included: • Built and scaled an end-to-end Generative AI platform using LLMs (OpenAI, LLaMA), RAG, and LangChain + LangGraph, delivering 60% faster innovation and 80% cost reduction. • Developed enterprise AI strategy aligned to OKRs and collaborated with C-suite to deliver AI-led transformation. • Designed PEFT pipelines using LoRA and QLoRA, and deployed optimized inference via TensorRT on NVIDIA GPUs. • Established a world-class AI Center of Excellence, mentoring engineers and data scientists globally. • Championed Responsible AI with robust governance frameworks to ensure ethical, fair, and explainable AI.

Building 1. Multi-Agentic AI Solutions 2. Data Products & Platforms

Prevalent AI, is a Cyber Security company and we were designing and developing a cyber security based data science platform named “Security Data Science” (SDS) to identify, correlate various threat sources in the domain by leveraging the most suitable machine learning and advanced analytics concepts and tools. My specific responsibilities were: • Delivered ML pipelines in the cybersecurity domain with 30% efficiency improvement • Led model governance and ethical AI adoption initiatives • Create road map for “Security Data Science” platform by incorporating Prevalent AI’s product vision • Generate end to end data science workflow in the Apache Metron cyber security platform • Developing, implementing and testing Data Science Proof of concept in the Apache Metron cyber security platform to evaluate the “Security Data Science” platform workflow • Identification of 56 Cyber security data sources and establishing relationship between each of them • Time series data analysis using Elastic Search X-Pack components • Anomaly detection model development using k-nearest neighbors (KNN) algorithm • Feature engineering – using chi-square test and model-based techniques • Text mining and Natural language processing using NLTK packages in the threat data sources • Conversion of Models to production able solutions using Python packages and Flask Web Server • Collaborate with Data Science and Big Data development teams to ensure optimized development process

CSCADE, a FedEx corporate flag ship program designed to reduce the global shipment caging by introducing the best-in-class solutions using historical information FedEx has and by correcting, correlating, learning and leveraging most suitable advanced analytics concepts available in the Data Science industry. My specific responsibilities were: • Interact with client representatives to determine the data science project’s scope and working with cross functional teams and vendors • Identify, understand and transform System Requirements in FedEx’s caging and clearance operations • Proof of Concept development to investigate and understand the challenges during the assessment and development phases to strategize the plan well in advance • Development of data science standards and guidelines, defining model deployment strategy and identification of model re-calibration techniques • Exploratory data analysis, data cleansing and munging, model development, selection, testing and implementation using data science techniques, practices and tool sets • Model development using Classification and Regression Trees (CART) and Random Forest • Feature engineering – using chi-square test and model based techniques • Text mining and Natural language processing using NLTK packages • Collaborate with Data Science and Big Data development teams to ensure optimized development process • Work with testing team to ensure the solutions meet FedEx business requirements.

• Solution design • Tool selection • Statistical, Quantitative and Predictive Analysis and Modelling • Extract, ingest, interpret, analyze, model and report diverse data sets • Data Visualization • Database and Application Performance Analysis and Tuning • Data Mining and Cleansing • Machine Learning implementation

• Exploratory Data analysis • Data cleansing and wrangling • Solution design • Tool selection • Cluster and Principal component analysis • Statistical, Quantitative and Predictive Analysis and Modelling • Extract, ingest, interpret, analyze, model and report diverse data sets • Data Visualization • Database and Application Performance Analysis and Tuning • Data Mining and Cleansing • Machine Learning implementation

• Interaction with the Business teams and streamline the business process • Discussion on the most suitable architectural approach required based on ERS’s Business requirement • Unit Testing and Integration Testing • Implementation planning on Development, Testing and Production environments

• Discussion with client on the most suitable architectural approach required for the Business • Develop architectural models and finalization of the architectural model • Application Design discussion and provide guidelines to team • Documentation and Sign Off from Client on the Architectural and design approaches • Governance Model Implementation • Implementation planning on Development, Testing and Production environments • tools and component development initiations and detailed discussions • Process and Performance optimization of the tools development • Global Deployment design and planning • Configuration Management

Technical Design & Architecture Software Design & Architecture Guidelines Mentoring Research and Development

Desin and Development