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I am Mythresh Neerugattu, an AI Engineer and Data Analyst with 4+ years of experience designing and deploying machine learning models, NLP pipelines, and AI-driven solutions across financial and enterprise domains. I specialize in Python, SQL, and Prefect to build scalable ETL workflows, data processing, and predictive analytics. I create and fine-tune models using XGBoost, Random Forest, LangChain, and LLMs to improve forecasting, semantic search, and compliance automation. I visualize KPIs with Power BI and Tableau to support data-driven decisions. As a collaborative Agile teammate, I deliver robust AI solutions using RAG techniques, vector databases, and prompt engineering to drive operational efficiency and innovation.…I am Mythresh Neerugattu, an AI Engineer and Data Analyst with 4+ years of experience designing and deploying machine learning models, NLP pipelines, and AI-driven solutions across financial and enterprise domains. I specialize in Python, SQL, and Prefect to build scalable ETL workflows, data processing, and predictive analytics. I create and fine-tune models using XGBoost, Random Forest, LangChain, and LLMs to improve forecasting, semantic search, and compliance automation. I visualize KPIs with Power BI and Tableau to support data-driven decisions. As a collaborative Agile teammate, I deliver robust AI solutions using RAG techniques, vector databases, and prompt engineering to drive operational efficiency and innovation.

Mythresh Neerugattu

Data Scientist, AI Engineer, Data Analyst, +2

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I am Mythresh Neerugattu, an AI Engineer and Data Analyst with 4+ years of experience designing and deploying machine learning models, NLP pipelines, and AI-driven solutions across financial and enterprise domains. I specialize in Python, SQL, and Prefect to build scalable ETL workflows, data processing, and predictive analytics. I create and fine-tune models using XGBoost, Random Forest, LangChain, and LLMs to improve forecasting, semantic search, and compliance automation. I visualize KPIs with Power BI and Tableau to support data-driven decisions. As a collaborative Agile teammate, I deliver robust AI solutions using RAG techniques, vector databases, and prompt engineering to drive operational efficiency and innovation.…I am Mythresh Neerugattu, an AI Engineer and Data Analyst with 4+ years of experience designing and deploying machine learning models, NLP pipelines, and AI-driven solutions across financial and enterprise domains. I specialize in Python, SQL, and Prefect to build scalable ETL workflows, data processing, and predictive analytics. I create and fine-tune models using XGBoost, Random Forest, LangChain, and LLMs to improve forecasting, semantic search, and compliance automation. I visualize KPIs with Power BI and Tableau to support data-driven decisions. As a collaborative Agile teammate, I deliver robust AI solutions using RAG techniques, vector databases, and prompt engineering to drive operational efficiency and innovation.

Available to hire

I am Mythresh Neerugattu, an AI Engineer and Data Analyst with 4+ years of experience designing and deploying machine learning models, NLP pipelines, and AI-driven solutions across financial and enterprise domains. I specialize in Python, SQL, and Prefect to build scalable ETL workflows, data processing, and predictive analytics. I create and fine-tune models using XGBoost, Random Forest, LangChain, and LLMs to improve forecasting, semantic search, and compliance automation. I visualize KPIs with Power BI and Tableau to support data-driven decisions. As a collaborative Agile teammate, I deliver robust AI solutions using RAG techniques, vector databases, and prompt engineering to drive operational efficiency and innovation.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Work Experience

Database Engineer (AI Focus) at JP Morgan Chase & Co.

June 1, 2024 - Present

Designed relational database schemas and created 200+ SQL Server/PostgreSQL tables, stored procedures, and functions to support enterprise-level financial operations and reporting. Developed and optimized high-performance stored procedures and ETL pipelines using SQL, Python, and Prefect, improving data refresh cycles and batch processing efficiency by 35%. Developed and deployed machine learning models (XGBoost, Logistic Regression, Random Forest) for financial forecasting, improving churn and delinquency prediction accuracy by 22%, using performance metrics for model validation.

AI Content Specialist and Evaluator at Outlier

March 1, 2025 - October 25, 2025

Conducted quality evaluations and HITL training for multimodal AI models in NLP, reinforcement learning, and creative content generation, improving output accuracy and contextual relevance. Applied advanced prompt engineering techniques to refine LLM responses, enhancing coherence, instruction following, and task-specific performance across projects, and delivered critical insights and iterative refinements to optimize model performance, aligning with client objectives and industry best practices.

Data Analyst at Dell Technologies

July 1, 2022 - October 25, 2025

Led data-driven capacity planning using Python (Pandas, NumPy, SciPy, Matplotlib) for predictive modeling, time series forecasting, and regression analysis, enhancing forecast accuracy and executive decisions. Developed classification models in Scikit-learn to predict request urgency, improving ticket routing by 15%; implemented ML algorithms (XGBoost, Random Forest) to identify system bottlenecks and increase infrastructure utilization by 20%. Executed advanced ETL processes and complex SQL queries on SQL Server and data warehouses to extract, transform, and analyze large-scale operational data across business functions. Designed and deployed interactive Tableau dashboards to monitor KPIs such as system uptime, support ticket trends, and SLA compliance, cutting manual reporting by 40%.

Data Science Intern at Konigtronics Pvt Ltd

May 1, 2021 - October 25, 2025

Preprocessed, normalized, and cleansed time-series sensor data using Python (Pandas, NumPy) on Linux systems, improving data accuracy by 25% and enabling efficient anomaly detection. Built GPU-accelerated predictive maintenance models in PyTorch and CUDA, integrating OpenCL kernels for specific compute tasks, reducing downtime by 20% and supporting collaborative development in Agile sprints.