Saad Siddiqui
EXPERTISE
BIO
I'm a Lead Data Scientist and Machine Learning Engineer with 10+ years of experience building and deploying AI/ML systems across telecom, healthcare, and finance. I specialize in LLM applications, deep learning, NLP, and end-to-end ML pipelines. At Afiniti, I led the development of a RAG-based ChatGPT platform, agentic video generation workflows, and AI-driven call analytics. My background also includes recommender systems, real-time optimization, and cloud-native deployment. I'm currently pursuing an MS in Computer Science (ML specialization) from Georgia Tech with a 3.9 GPA.
WORK EXPERIENCE
Lead Data Scientist
Afinti
September 2022 - Present
•Designed and deployed a RAG-based ChatGPT system with semantic search, leveraging Pinecone for scalable vector-based document retrieval. •Enhanced query accuracy through advanced metadata filtering and LLM-based reranking, improving relevance for the Cloud Operations Platform Team. •Developed a fully automated faceless video generation pipeline using agentic AI workflows to streamline marketing content production. •Engineered an AI-powered call analytics platform for retail, applying speech-to-text and NLP to extract actionable insights from customer conversations. •Integrated sentiment analysis, intent detection, and automated reporting to enhance customer experience and operational strategy. •Built and maintained robust, end-to-end data pipelines supporting seamless data ingestion, transformation, and model deployment at scale. •Facilitated stakeholder workshops to align AI initiatives with underwriting and product strategies, driving measurable business outcomes. •Mentored cross-functional teams on Agile practices, fostering iterative development, faster delivery, and continuous process improvement
Senior Data Scientist - Applied AI
Afinti
February 2022 - September 2022
Developed price elasticity and retention models for auto and property insurance to quantify premium sensitivity and predict policy renewal behavior. •Leveraged historical policy, claims, and pricing data to optimize underwriting strategies and improve customer lifetime value. •Led the development of a credit risk assessment model using ensemble machine learning techniques, •improving default prediction accuracy by 18% and reducing loan loss provisions by $15M annually. •Designed and implemented predictive models such as Bankruptcy Prediction for the Order to Cash team, •resulting in improved risk management and reduced financial discrepancies, achieving a 10% reduction in bad debt ratio. •Implemented an NLP-based email classification system using word embeddings to categorize service requests and improve customer support efficiency. •Led the development of an Unauthorised Utilisation Detection System for Visi Coolers using computer vision and OpenCV techniques
EDUCATION
Master of Science
Georgia Institute of Technology, February 2025
Computer Science
Verified Machine Learning Engineer
8+ years of experience
Preferred commitment: Full Time
Languages
Skills
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