Chitresh Kaushik

Data Scientist

Rewari, Haryana, India5 yrs 2 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Expert in Generative AI and RAG systems.
Proven track record in time series forecasting.
Skilled in developing intelligent agent systems.

Stackforce AI infers this person is a Generative AI Engineer specializing in AI-driven solutions for enterprise applications.

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Skills

Core Skills

Generative AiRetrieval-augmented Generation (rag)Time Series ForecastingNatural Language Processing (nlp)

Other Skills

LLMOpsData-Driven Decision SystemsPythonFastAPIRAG SystemsLangGraphLangChainRESTful APIsText AnalyticsData StructuresAzure FunctionsAzure AI SearchAzure Cosmos DBPrompt DesignREST APIs

About

• Generative AI Engineer & Data Scientist with around 5 years of experience spanning Natural Language Processing (NLP), Time Series Forecasting, and Applied Machine Learning, including 2 years dedicated to Generative AI innovations. • Skilled in designing and deploying Retrieval-Augmented Generation (RAG) systems, LangGraph and LangChain-based agentic workflows, and LLMOps pipelines for large-scale model lifecycle management. • Experienced in developing Speech-to-Text (STT) and multimodal AI applications using the Azure AI ecosystem, integrating conversational intelligence with contextual retrieval. • Proficient in deep learning, predictive modeling, and data-driven decision systems, supported by a strong foundation in statistics, Python, and modern ML frameworks. Passionate about advancing the boundaries of LLM engineering and AI reasoning, I aim to build scalable, intelligent systems that bridge the gap between research and real-world enterprise impact — driving automation, understanding, and innovation in the age of Generative AI.

Experience

5 yrs 2 mos

Total Experience

2 yrs 6 mos

Average Tenure

3 yrs 9 mos

Current Experience

Ibm

2 roles

Data Scientist

Sep 2022 – Present · 3 yrs 9 mos · Hybrid

Engineered production-grade GenAI applications leveraging RAG architectures and LLM orchestration frameworks.
Designed intelligent agent systems enabling autonomous reasoning and workflow automation.
Built forecasting pipelines using Time Series models to support data-driven operational decision-making.
Developed semantic retrieval systems using embeddings, metadata enrichment, and vector search.
Improved model performance through prompt optimization, evaluation frameworks, and scalable inference design.
Delivered enterprise AI solutions aligned with real-world business use cases.

Generative AIRetrieval-Augmented Generation (RAG)LLMOpsTime Series ForecastingData-Driven Decision Systems

Data Scientist

Sep 2022 – Feb 2026 · 3 yrs 5 mos · Hybrid

Sep 2022 – May 2024 | Time Series Forecasting & HR Analytics
Developed and deployed time series forecasting pipelines for HR analytics, improving accuracy and scalability of workforce planning models.
Implemented advanced techniques including ARIMA, Dynamic Linear Models, and Reinforcement Learning for supply forecasting optimization.
Led feature integration and model testing, acting as the main point of contact for pipeline enhancements.
Delivered executive-level analyses and dashboards, driving data-informed decision-making.
Built Responsible AI POCs to assess ethics, bias, and explainability in forecasting models.
Jun 2024 – Present | Generative AI, RAG Systems & LLMOps
Designing Agentic RAG pipelines and LLM-powered automation using LangGraph, LangChain, and Azure AI.
Developed FastAPI microservices for scalable GenAI workflow orchestration and model serving.
Built voice-enabled chatbot systems with Azure Speech Studio for real-time Speech-to-Text (STT) interactions.
Implemented LLMOps for model monitoring, evaluation, and lifecycle management.
Engineered multilingual email generation and retrieval workflows, enhancing automation across customer support systems.

PythonFastAPITime Series ForecastingGenerative AIRAG SystemsLLMOps

Wipro limited

Junior Data Scientist

Feb 2018 – Jul 2019 · 1 yr 5 mos · Pune Division, Maharashtra, India

Worked as a Junior Data Scientist focusing on Natural Language Processing (NLP), contributing to the design, development, and deployment of text analytics and machine learning solutions for enterprise applications.
Built and fine-tuned text classification, sentiment analysis, and named entity recognition (NER) models using Python, NLTK, spaCy, and scikit-learn.
Conducted data preprocessing, feature engineering, and model performance evaluation on large-scale unstructured text data to enhance accuracy and generalization.
Developed and deployed RESTful APIs to serve trained NLP models, enabling seamless integration of AI capabilities into business applications.
Collaborated with data engineering and backend teams to containerize models using Flask and Docker for scalable deployment.
Explored word embeddings (Word2Vec, GloVe) and LSTM-based architectures for advanced text understanding.

Natural Language Processing (NLP)PythonRESTful APIsText Analytics