Abhik Debnath

AI Researcher

Bengaluru, Karnataka, India6 yrs 9 mos experience

AI ML PractitionerHighly Stable

Key Highlights

Expert in deploying Generative AI systems at scale.
Proven track record of reducing project timelines significantly.
Strong background in machine learning across multiple domains.

Stackforce AI infers this person is a Data Scientist specializing in Generative AI and Machine Learning solutions for FinTech and Marketing.

Contact

Skills

Core Skills

Generative AiLarge Language Models (llm)Natural Language Processing (nlp)Azure MlMachine LearningData Analysis

Other Skills

A/B TestingAWS SageMakerAmazon Web Services (AWS)Apache AirflowAzure Data FactoryAzure DatabricksDSADeep LearningGitGoogle OR-ToolsHyperparameter OptimizationIsolation ForestJupyterLangChainMicrosoft Azure

About

I am a Data Scientist with 6 years of experience building scalable AI and ML solutions that address real-world business problems. My work spans traditional machine learning, deep learning, NLP, and Generative AI across domains such as FinTech, Sales, Marketing and Software Engineering. In recent years, I’ve focused on building and deploying Generative AI systems using large language models. These include tools for content generation, aspect based sentiment analysis, test automation, and RAG pipelines. I’ve worked extensively with prompting techniques, fine-tuning of open-source LLMs, and building multi-agent architectures for complex task orchestration. My approach is hands-on and outcome-driven, from building prototypes to deploying solutions in production on cloud platforms. I was involved in cross-functional projects that have resulted in measurable impact and significant efficiency gains. I hold dual post-graduate degrees from IIT Madras and IIT Kharagpur, and I’m deeply interested in applying AI responsibly at scale.

Experience

6 yrs 9 mos

Total Experience

3 yrs

Average Tenure

9 mos

Current Experience

Razorpay

Senior Data Scientist

Aug 2025 – Present · 9 mos · Bengaluru, Karnataka, India · On-site

- Working as a part of the Central Data Science Team

Bosch research

Senior Data Scientist

Jan 2023 – Aug 2025 · 2 yrs 7 mos · Bengaluru, Karnataka, India · On-site

Part of multiple GenAI initiatives across Bosch's business units, deploying production-grade solutions using LLMs.
Built JENNY, a GPT-powered content generation platform that reduced marketing and website content creation time from months to days, resulting in huge annual savings.
Developed an LLM-based Aspect-Based Sentiment Analysis (ABSA) engine for Bosch Power Tools product reviews, replacing legacy BERT models and reducing annotation overhead by a substantial amount annually.
Developed DIKE, a RAG platform with hybrid retrieval, re-ranking, and embeddings to deliver high-relevance document-grounded responses; scaled to 5GB+ corpora and designed for 1000+ users.
Developed a PoC for software test specification generation using multi-agent systems via AutoGen, ReAct, and CoT prompting, achieving 20–30% gains in specification generation.
Designed and deployed solutions using Azure ML, Streamlit, LangChain, and OpenAI APIs, ensuring scalability and business adoption.

Generative AILarge Language Models (LLM)Azure MLStreamlitLangChainOpenAI APIs

Bosch center for artificial intelligence (bcai)

Data Scientist

Jul 2019 – Dec 2022 · 3 yrs 5 mos · Bengaluru, Karnataka, India · On-site

Developed a linear optimization model using Google OR-Tools to recommend product assortments for deal events, incorporating price elasticity derived from log-log regression models.
Built a rule-based clustering framework to segment high-revenue products for targeted promotions using transactional and behavioral data.
Designed an anomaly detection system using Isolation Forest to flag underperforming keywords in ad campaigns, enabling proactive performance tuning.
Built field failure prediction models using Random Forest and interpretable ML (LIME, SHAP), enabling preventive maintenance and huge annual savings.
Led cross-functional collaborations and presented project outcomes through internal blogs, newsletters, and mentoring events including company-wide hackathons.

Machine LearningData AnalysisRandom ForestIsolation ForestGoogle OR-Tools