Senior Data Analyst & GenAI Engineer

Hruthik

************@*****.***

GenAI and Data Analyst

www.linkedin.com/in/hruthik-adari

Ph no: 682-***-****

Professional Summary:

Results-driven Senior Data Analyst and Generative AI Engineer with experience delivering AI, machine learning, and analytics solutions across telecom, healthcare, and financial domains.

Skilled in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Generative AI, Natural Language Processing (NLP), and predictive analytics.

Hands-on expertise in Python, SQL, LangChain, OpenAI APIs, Hugging Face Transformers, Java, and cloud platforms including AWS and Google Cloud Platform (GCP).

Experienced in developing scalable AI/ML pipelines using Vertex AI, BigQuery, Cloud Functions, Kubernetes, Docker, and CI/CD workflows.

Proficient in building conversational AI systems, multi-agent AI applications, intelligent automation workflows, and context-aware enterprise search solutions.

Strong background in data analytics, ETL development, data modeling, dashboard reporting, and business intelligence using Power BI and Tableau.

Skilled in vector databases and AI retrieval systems including FAISS and Pinecone for enterprise-grade RAG applications.

Experienced in machine learning, reinforcement learning, statistical analysis, and data-driven decision-making methodologies.

Knowledgeable in cloud architecture, microservices, API integration, and scalable production deployment of AI platforms.

Strong understanding of data governance, IAM, encryption, DLP, GDPR, and CCPA compliance standards for secure AI and analytics solutions.

Proven ability to collaborate with cross-functional teams in Agile environments to deliver high-impact, business-focused technology solutions.

Technical Skills:

Programming Languages: Python, SQL

Python Libraries: Pandas, NumPy, SciPy, Scikit-learn, Matplotlib, Seaborn, Plotly

Machine Learning & AI: Linear Regression, Logistic Regression, SVM, KNN, Random Forest, XGBoost, K-Means,Deep Learning

Generative AI & LLMs: OpenAI GPT (2/3), Hugging Face Transformers

NLP Techniques: Sentiment Analysis, Keyword Extraction, Entity Recognition, Document Classification, Text Summarization

Data Processing & ETL: Pandas, NumPy, SQLAlchemy, PySpark

Visualization & Reporting: Tableau, Power BI, Matplotlib, Seaborn, Excel, PowerPoint

Backend & API Development: Flask, Django, REST APIs, Third-party API Integration

Cloud Platforms: AWS (EC2, S3, RDS), Azure, Google Cloud Platform (GCP - Vertex AI, BigQuery, Cloud Functions)

Database Management: PostgreSQL, MySQL, SQL Server, MongoDB

Version Control: Git, GitHub

Tools & Workflow: Jupyter Notebook, VS Code, Azure Data Factory, Airflow, DBT

Education Details:

Master of Science in Data Analytics, Concordia University, St. Paul, Minnesota.

2023-2024

Bachelor of Science in Instrumentation Technology, Andhra University.

2017-2021

Work Experience:

Senior Data Analyst at Tata Consultancy Services, Plano, TX May 2026 – Present

Client: AT&T

Supporting enterprise-scale analytics and AI initiatives for AT&T by developing data-driven solutions to improve operational efficiency and business intelligence reporting.

Designing and optimizing ETL/data pipelines using SQL, Python, and cloud technologies for large-scale structured and semi-structured telecom datasets.

Developing AI-powered analytics workflows using Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) frameworks to automate insights generation and knowledge retrieval.

Utilizing machine learning and predictive analytics techniques to identify trends, improve reporting accuracy, and support strategic decision-making.

Building interactive dashboards and automated reports using Power BI/Tableau to provide actionable business insights for stakeholders.

Collaborating with cross-functional engineering and business teams in Agile environments to deploy scalable analytics and AI solutions.

Applying cloud and AI technologies including AWS, GCP, Vertex AI, LangChain, OpenAI APIs, and vector databases to support intelligent enterprise applications.

Implementing data governance, security, and compliance controls including IAM, encryption, and data privacy standards for enterprise data platforms.

GenAI Engineer at Eternal Hill Services LLC., Dallas, TX June 2024 – April 2026

Client: Takeda Pharmaceutical Company

Designed and implemented scalable Generative AI pipelines on Google Cloud Platform (GCP) using Vertex AI, BigQuery, Cloud Storage, and Cloud Functions for processing large-scale structured and unstructured datasets.

Developed and fine-tuned Large Language Models (LLMs) using Vertex AI custom training and managed endpoints to build domain-specific chatbots and text summarization applications.

Engineered multi-agent AI systems using LangChain with Python and Java integrations to enable autonomous task execution and collaborative decision-making workflows.

Built reinforcement learning prototypes using Q-Learning and PPO in OpenAI Gym for intelligent optimization and adaptive decision-making applications.

Applied symbolic AI and knowledge representation techniques to improve reasoning, planning, and explainability in conversational AI systems.

Architected fault-tolerant AI platforms on GCP and AWS using containerized microservices, Kubernetes, Docker, and CI/CD pipelines for scalable production deployments.

Developed advanced Retrieval-Augmented Generation (RAG) solutions by integrating FAISS and Pinecone vector databases with document ingestion pipelines for context-aware enterprise search and knowledge management systems.

Leveraged LangChain, OpenAI APIs, Hugging Face Transformers, and prompt engineering techniques to create conversational AI assistants with memory, multi-turn dialogue, and real-time data retrieval capabilities.

Implemented AI governance, encryption, IAM policies, and DLP integrations to ensure GDPR and CCPA compliance during LLM training and inference workflows.

GenAI Engineer – Guardant Health, USA April 2023 – Feb 2024

Utilized Python, statistical analysis, machine learning, and AI methodologies to support healthcare-focused analytics solutions.

Worked with Large Language Models (LLMs), NLP techniques, and Retrieval-Augmented Generation (RAG) architectures to develop intelligent applications for data analysis and automation.

Prepared and embedded datasets designed retrieval workflows, and optimized prompts to improve context-aware model outputs and response quality.

Evaluated AI model performance and contributed to improving scalability, reliability, explainability, and inference accuracy.

Supported development of scalable Generative AI systems for predictive analytics, workflow automation, and enhanced clinical/business decision-making.

Data Analyst, HDFC Credila Financial Services Limited, India July 2021 – August 2022

Analyzed financial and operational datasets to generate actionable business insights and improve reporting accuracy.

Developed dashboards and reports using SQL, Excel, and BI tools to support data-driven business decisions.

Performed data cleaning, transformation, and validation to improve data quality, consistency, and reporting efficiency.

Assisted in predictive analytics and trend analysis initiatives to support risk assessment and operational planning.

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