I am an AI/ML Engineer with 4 years of experience designing, developing, and deploying machine learning and deep learning solutions, with additional expertise as a Data Scientist. I thrive in fast-paced environments, translating statistical analysis, data engineering, and NLP into actionable insights to support data-driven decision-making. I am proficient in Python, TensorFlow, Scikit-learn, PyTorch, SQL, and cloud platforms (AWS, Azure), with hands-on experience in MLOps for scalable deployment. I build predictive models, optimize large-scale data pipelines, and apply NLP and LLM-based solutions for advanced analytics, delivering real-time predictions with low latency and high reliability across financial services and technology domains.

Praneeth Karra

I am an AI/ML Engineer with 4 years of experience designing, developing, and deploying machine learning and deep learning solutions, with additional expertise as a Data Scientist. I thrive in fast-paced environments, translating statistical analysis, data engineering, and NLP into actionable insights to support data-driven decision-making. I am proficient in Python, TensorFlow, Scikit-learn, PyTorch, SQL, and cloud platforms (AWS, Azure), with hands-on experience in MLOps for scalable deployment. I build predictive models, optimize large-scale data pipelines, and apply NLP and LLM-based solutions for advanced analytics, delivering real-time predictions with low latency and high reliability across financial services and technology domains.

Available to hire

I am an AI/ML Engineer with 4 years of experience designing, developing, and deploying machine learning and deep learning solutions, with additional expertise as a Data Scientist. I thrive in fast-paced environments, translating statistical analysis, data engineering, and NLP into actionable insights to support data-driven decision-making. I am proficient in Python, TensorFlow, Scikit-learn, PyTorch, SQL, and cloud platforms (AWS, Azure), with hands-on experience in MLOps for scalable deployment.

I build predictive models, optimize large-scale data pipelines, and apply NLP and LLM-based solutions for advanced analytics, delivering real-time predictions with low latency and high reliability across financial services and technology domains.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
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Language

English
Fluent

Work Experience

AI/ML Engineer at State Street
April 1, 2024 - Present
Designed and deployed ML models to predict fraudulent transactions and credit risk, improving detection accuracy by 21%. Developed data ingestion pipelines using Apache Airflow and AWS Glue to process large-scale financial datasets from multiple sources, improving data availability by 40% and reducing integration errors by 25%. Engineered data preprocessing workflows in Pandas and PySpark to enhance model training efficiency, reducing processing time by 30% and increasing pipeline throughput by 20%. Implemented NLP algorithms in SpaCy & Hugging Face Transformers to extract entities from financial documents, contracts, and reports, accelerating document analysis. Developed and trained deep learning models (CNN, RNN) for pattern recognition in transaction data, leveraging transfer learning to detect anomalies and reduce false positives. Deployed ML models as RESTful APIs using Flask & Docker on AWS SageMaker, enabling real-time fraud detection and credit scoring with sub-200ms latency an
Data Scientist at Hexaware Technologies
June 30, 2023 - October 15, 2025
Built predictive models using Python (scikit-learn) to identify customer churn and retention strategies, improving retention. Fine-tuned and optimized Large Language Models (LLMs) using prompt engineering and transfer learning to improve contextual accuracy and deliver domain-specific insights. Automated ETL workflows in Python and SQL, streamlining data preprocessing and reducing pipeline runtime by 35%. Conducted exploratory data analysis (EDA) and applied statistical techniques to uncover business insights from structured and unstructured datasets. Employed ML models (Random Forest, KNN, Naive Bayes) to optimize loan approval processes, reducing default rates by 20% and improving portfolio profitability. Applied NLP techniques (sentiment analysis) using Azure Cognitive Services to analyze customer feedback, driving improved service strategies. Optimized time-series forecasting models for demand prediction with good forecast accuracy. Created interactive dashboards in Tableau and Pow

Education

Master of Science in Information Technology at University of Cincinnati, USA
January 11, 2030 - December 1, 2024

Qualifications

AWS Certified Solutions Architect – Associate
January 11, 2030 - October 15, 2025
Microsoft Certified: Azure Data Scientist Associate (DP-100)
January 11, 2030 - October 15, 2025

Industry Experience

Financial Services, Software & Internet, Professional Services