S Karthikeyan

Data Scientist

Chennai, Tamil Nadu, India5 yrs 3 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in Generative AI and NLP solutions.
Proven track record in enhancing chatbot performance.
Strong background in fraud detection and recommendation systems.

Stackforce AI infers this person is a Data Scientist specializing in AI-driven solutions for Fintech and SaaS industries.

Contact

Skills

Core Skills

Generative AiNatural Language Processing (nlp)Deep LearningArtificial Intelligence (ai)Data Analytics

Other Skills

Data SciencePython (Programming Language)Amazon Web Services (AWS)Cloud ComputingAgentic AIHDBSCANPCAUMAPRAGAmazon Lexk-means clusteringLinear ModelsFine TuningTransformersCross Encoderss

About

As a Data Scientist at Tiger Analytics, I specialize in building production-grade solutions using Generative AI, LLM-based intent classification, and RAG architectures. My recent work includes enhancing chatbot performance with GPT-4 Turbo and FAISS-powered fallback recovery, improving user experience through better intent resolution, and optimizing customer insights using unsupervised techniques like HDBSCAN and UMAP. Previously, I contributed to Shell's data-driven transformation as an Associate Data Scientist by developing clustering models and semi-supervised BERT pipelines that reduced manual effort and improved accuracy across large-scale datasets. My early foundation was shaped at LTI Mindtree and Kanini, where I deployed real-time fraud detection systems and built scalable recommender engines. Armed with a B.E. from the Government College of Technology, Coimbatore, and advanced certifications from Imarticus, UCLA, and Scaler, I combine deep technical knowledge with a product-focused mindset to deliver business impact through AI.

Experience

5 yrs 3 mos

Total Experience

1 yr

Average Tenure

3 mos

Current Experience

Swiggy

Data Scientist 2

Feb 2026 – Present · 3 mos · Bengaluru, Karnataka, India · Hybrid

Tiger analytics

Data Scientist

Aug 2024 – Feb 2026 · 1 yr 6 mos · Chennai, Tamil Nadu, India · Hybrid

Designed and deployed a robust enhancement pipeline for chatbot performance and fallback recovery.
Utilized HDBSCAN clustering with PCA/UMAP for intent overlap resolution, boosting accuracy by 8%.
Architected a RAG-based fallback system on Amazon Lex, improving ambiguous query handling significantly.
Automated bot testing via AWS Lambda, ensuring consistent quality across versions.

Data SciencePython (Programming Language)Generative AINatural Language Processing (NLP)Deep LearningAmazon Web Services (AWS)+2

Shell

Associate data scientist

Jul 2023 – Jun 2024 · 11 mos · Chennai, Tamil Nadu, India · Hybrid

Enhanced operational efficiency by clustering users based on invoice features using K Prototype and DBSCAN algorithms.
Achieved a 30% reduction in invoice processing time and a 15% improvement in overall efficiency.
Developed a semi-supervised learning pipeline, automatically labeling over 150K support tickets, reducing manual workload by 80%.
Contributed to Shell's innovative approach in data science to optimize support operations in Chennai, Tamil Nadu.

k-means clusteringLinear ModelsFine TuningTransformersCross EncoderssAmazon Web Services (AWS)+3

Lti - larsen & toubro infotech

Associate Data scientist

May 2022 – Jul 2023 · 1 yr 2 mos · Chennai, Tamil Nadu, India

Developed and deployed a robust fraud detection system utilizing Isolation Forest and Local Outlier Factor techniques.
Implemented Docker for scalable and consistent deployment, enabling real-time monitoring of transactions.
Created a personalized product recommendation system that increased customer engagement by 25% and improved sales conversion rates by 18%.
Contributed to LTI's mission of leveraging data science to enhance business operations and customer experiences.

Natural Language Processing (NLP)Data AnalyticsArtificial Intelligence (AI)Python (Programming Language)Statistical ModelingData Ingestion+9

Kanini

Junior Data Scientist

Oct 2021 – May 2022 · 7 mos · Chennai, Tamil Nadu, India

Developed and deployed end-to-end machine learning pipelines for attrition prediction, reducing customer churn by 22%.
Designed scalable data processing workflows for real-time feature ingestion and model retraining.
Implemented the full MLOps lifecycle using Docker and GitHub Actions to ensure automated deployment.
Created interactive Streamlit applications for stakeholders to visualize predictions and take proactive actions.

Natural Language Processing (NLP)DatacleaningData AnalyticsArtificial Intelligence (AI)Data CollectionAnalytical Skills+8