Varun Raste

AI Researcher

Mumbai, Maharashtra, India6 yrs 4 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in MLOps and Generative AI solutions.
Proven track record in driving enterprise AI sales.
Strong background in statistical analysis and data science.

Stackforce AI infers this person is a Data Science and AI Solutions expert with a focus on enterprise applications.

Contact

Skills

Core Skills

MlopsGenerative AiConversational AiNatural Language Processing (nlp)Machine LearningFraud Detection

Other Skills

Redhat Openshift AISalesTechnical SolutioningStakeholder EngagementRetrieval-Augmented GenerationChatbot DevelopmentLarge Language ModelOpenShift AILangChainAzure AI SearchJIRAOpen AI ModelsSurvival AnalysisXGBoostBERT

About

Graduated with a Master's in Financial Engineering from WorldQuant University, complemented by a robust academic foundation in statistics and analytics. Currently contributing to IBM as a Solution Specialist Architect, focusing on enterprise AI solution selling through expertise in MLOps and Red Hat OpenShift AI. Passionate about delivering impactful Machine Learning and Generative AI solutions, collaborating with stakeholders on technical solutioning, and developing Proof of Concepts to showcase platform capabilities. Dedicated to combining technical proficiency with business acumen to drive innovative AI-driven strategies.

Experience

Ibm

Solution Specialist Architect (Data Scientist - Presales)

Jul 2025 – Present · 8 mos · Mumbai · Hybrid

As a Data Scientist in the BTS Pre-Sales team, I drive enterprise AI solution selling by blending technical expertise with client engagement skills to deliver impactful Machine Learning (ML) and Generative AI (GenAI) solutions. I am currently working for their client ‘Redhat’
Key Responsibilities:
1. Serve as Subject Matter Expert (SME) for Red Hat OpenShift AI — an enterprise-grade MLOps platform for deploying, scaling, and managing ML and GenAI models in production.
2. Lead RFP management, technical solutioning, and stakeholder presentations, translating business requirements into AI-driven solutions.
3. Architect and develop Proof of Concepts (POCs) to showcase platform capabilities, including:
a. Retrieval-Augmented Generation (RAG) chatbot for client-specific FAQ automation.
b. Large Language Model (LLM) deployment and optimization on OpenShift AI.
4. Manage end-to-end model lifecycle: model development, deployment, monitoring, and performance optimization.
5. Conduct workshops, discovery sessions, and platform enablement programs to increase adoption and demonstrate ROI to enterprise clients.
6. Collaborate with the sales team to align AI/ML solution design with revenue generation and go-to-market strategies.
Impact & Achievements:
Successfully delivered AI/ML demonstrations that accelerated client adoption of OpenShift AI across industries.
Enhanced pre-sales conversion rates by combining technical proofs with business value mapping.
Contributed to measurable revenue growth through strategic AI/ML solution pitches and deployments.

MLOpsRedhat Openshift AIGenerative AISalesTechnical SolutioningStakeholder Engagement

Fractal

2 roles

Data Scientist- Gen AI

Dec 2024 – Jun 2025 · 6 mos · Mumbai, Maharashtra, India · Hybrid

1. Worked on Conversational AI chatbot for a big investment firm client , Used tools like JIRA , Langchain , VS Code , Bibucket , Azure AI Search, Pydantic-AI , Open AI models for implementation purpose.
2. Built a search engine for user queries where user can ask details of a particular fund and he/she will be giving the corresponding document & summary of the document as result.
3. This application helped business stakeholders (specifically sales team) where they could utilize a chatbot in order to get summary and documents for the searched funds

LangChainAzure AI SearchConversational AIJIRAOpen AI Models

Data Scientist -AIML

Sep 2022 – Dec 2024 · 2 yrs 3 mos · Mumbai, Maharashtra, India · Hybrid

1. Developed a Q&A bot for internal employee policies using local LLMs like GPT4all and vector bases like chromaDB, deployed it with Streamlit.
2. Worked on brand extraction with OpenAI's GPT-4 and Llama 2 models, resulting in 92% accuracy and an 8% improvement over the existing regex approach.
3. Automated insights generation with Python and Gen AI, saving effort equivalent to 2 FTEs per week.
4. Developed a solution to proactively target customers before they run out of detergent using ML algorithms like XGBoost & SVR, leveraging Survival regressions for repurchase calculations and employing panel regression for feature interpretability through hypothesis testing.
5. Implemented sentiment classification for client product reviews using advanced models like BERT and various embeddings, and performed topic modeling (LDA, BERT) on the review corpus to identify important themes from liked and disliked reviews.
6. Developed household propensity models using a multi-touch attribution method, incorporating Bayesian regression, odds analysis, and household profiling based on impressions and transactions, resulting in a 20% improvement over the existing lead generation model. Led marketing mix modeling project, optimizing marketing investments to drive ROI across diverse industries.
7. Played a key role in developing the Fractal Coursera Data Science Specialization, serving as a Subject Matter Expert (SME) for content creation focused on Python topics, and designed and delivered an end-to-end Gen AI course titled 'Gen AI - Your Code Reviewer'.

Natural Language Processing (NLP)Machine LearningSurvival AnalysisXGBoostBERT

Hdfc bank

Manager - Credit Analytics and Innovation (Fraud & Bureau Analytics)

Jun 2021 – Sep 2022 · 1 yr 3 mos · Mumbai, Maharashtra, India · Hybrid

1, Managed end-to-end delivery of fraud, bureau analytics projects involving data science execution & strategic implementation ensuring an effective interaction with business stakeholders.
2. Built fraud identification and early delinquency detection models using machine learning algorithms such as XGBoost and Catboost for consumer durables and two-wheeler loan portfolios, achieving a 35% lift for two-wheeler loans and a 32% lift for consumer durables compared to existing models. Deployed the solution with the assistance of Azure ML.
3. Collaborated with stakeholders on bureau initiatives, achieving a 30% uplift in risk classification for new-to-bank customers applying for two-wheeler loans.
4. Participated in Proof-of-Concept (POC) projects with bureaus to assess product testing and enhance understanding of bureau data quality.
5. Handled ad-hoc assignments, including model monitoring, identification of fraudulent merchants, and customer segmentation for risk mitigation in auto loans.

Fraud DetectionRisk AssessmentXGBoostCatboost

Fiserv

2 roles

Senior Associate ,Statistical Analysis

Nov 2020 – Jun 2021 · 7 mos · Pune, Maharashtra, India

1. Applied machine learning techniques to analyze and predict customer attrition, utilizing data-driven insights to proactively detect and mitigate churn risk factors. This approach significantly improved retention strategies and enhanced customer engagement, yielding a model KS of 51%.
2. Utilized Python for time series forecasting, implementing SARIMA, prophet , LSTM , XGboost to predict future transactions with a model boasting 94% accuracy, providing valuable insights to stakeholders.
3. Leveraged deep learning techniques for Intelligent Character Recognition (ICR) and Optical Character Recognition (OCR) tasks, streamlining internal invoice text extraction and saving 2 FTE/week.
4. Developed an NLP-driven chatbot using the Rasa framework in Python, enhancing communication channels and user engagement.

Machine LearningTime Series AnalysisNLPPython