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I'm Manogna an AI Engineer with a decade of experience building machine learning and Generative AI solutions across banking, healthcare, and marketing. I design production-ready AI systems, automate business processes, and empower teams to make data-driven decisions. I translate complex challenges into scalable data platforms, collaborate with cross-functional partners, and deliver reliable, maintainable AI that users trust and adopt. I thrive on turning ideas into real-world impact via end-to-end ML pipelines, model governance, and continuous improvement.…I'm Manogna an AI Engineer with a decade of experience building machine learning and Generative AI solutions across banking, healthcare, and marketing. I design production-ready AI systems, automate business processes, and empower teams to make data-driven decisions. I translate complex challenges into scalable data platforms, collaborate with cross-functional partners, and deliver reliable, maintainable AI that users trust and adopt. I thrive on turning ideas into real-world impact via end-to-end ML pipelines, model governance, and continuous improvement.

Manogna

AI Engineer, Data Scientist, Full Stack Developer, +2

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I'm Manogna an AI Engineer with a decade of experience building machine learning and Generative AI solutions across banking, healthcare, and marketing. I design production-ready AI systems, automate business processes, and empower teams to make data-driven decisions. I translate complex challenges into scalable data platforms, collaborate with cross-functional partners, and deliver reliable, maintainable AI that users trust and adopt. I thrive on turning ideas into real-world impact via end-to-end ML pipelines, model governance, and continuous improvement.…I'm Manogna an AI Engineer with a decade of experience building machine learning and Generative AI solutions across banking, healthcare, and marketing. I design production-ready AI systems, automate business processes, and empower teams to make data-driven decisions. I translate complex challenges into scalable data platforms, collaborate with cross-functional partners, and deliver reliable, maintainable AI that users trust and adopt. I thrive on turning ideas into real-world impact via end-to-end ML pipelines, model governance, and continuous improvement.

Available to hire

I’m Manogna an AI Engineer with a decade of experience building machine learning and Generative AI solutions across banking, healthcare, and marketing. I design production-ready AI systems, automate business processes, and empower teams to make data-driven decisions.

I translate complex challenges into scalable data platforms, collaborate with cross-functional partners, and deliver reliable, maintainable AI that users trust and adopt. I thrive on turning ideas into real-world impact via end-to-end ML pipelines, model governance, and continuous improvement.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Work Experience

AI Engineer at Credit One

October 1, 2024 - Present

Designed and developed distributed data pipelines using AWS Glue, Amazon EMR, and PySpark to process large volumes of structured and semi-structured data for analytics and machine learning. Built end-to-end machine learning pipelines using Amazon SageMaker, supporting model training, deployment, monitoring, and continuous improvement. Designed and deployed Generative AI applications that enabled customer support and operations teams to quickly access internal policies, procedures, and knowledge using Retrieval-Augmented Generation (RAG). Built AI-powered assistants that automated routine support requests and reduced time spent searching enterprise documentation. Developed agentic AI workflows to automate multi-step business processes by combining enterprise knowledge, internal APIs, and business rules. Integrated AI applications with internal APIs and enterprise systems to deliver contextual responses and streamline business workflows. Developed scalable FastAPI services for serving ma

Machine Learning Engineer at Cigna

February 1, 2023 - September 1, 2024

Developed real-time and batch inference services using FastAPI, AWS Lambda, and Amazon API Gateway, supporting low-latency integrations with enterprise analytics platforms and clinical data applications. Provisioned and managed scalable cloud infrastructure on AWS (EC2, S3, ECR, ECS, EKS) to support containerized ML deployments, resource optimization, and production availability across healthcare workloads. Engineered machine learning solutions using Python, Scikit-learn, TensorFlow, and XGBoost, delivering predictive models for claims analytics, risk stratification, and intelligent process automation. Designed enterprise data pipelines and ETL frameworks using PySpark for large-scale distributed processing, ensuring high-quality data availability for model training and analytics consumption. Streamlined model training, evaluation, and deployment through AWS SageMaker, reducing iteration cycles and improving consistency across production machine learning environments. Automated workflo

Senior Data Scientist at Zeta Global

May 1, 2019 - November 1, 2022

Developed and optimized regression, classification, and clustering models using supervised and unsupervised learning techniques to support business intelligence and operational analytics across marketing and customer engagement platforms. Built Flask-based REST APIs for model deployment, enabling seamless integration of predictive outputs with enterprise reporting systems and external data consumers. Engineered time-series forecasting models to support demand planning, sales trend analysis, and long-range strategic decision-making for business stakeholders. Conducted exploratory data analysis using Pandas and NumPy to surface trends, data quality issues, and actionable insights for model development and operational reporting. Designed feature engineering workflows including normalization, encoding, and outlier handling to improve model quality and prediction reliability at scale. Processed large-scale structured and semi-structured datasets using PySpark, improving training efficiency

Data Scientist at Grid Dynamics

June 1, 2016 - April 1, 2019

Analyzed large-scale structured and unstructured datasets using Python, SQL, Pandas, and NumPy to uncover business trends, customer behavior patterns, and actionable insights. Developed and deployed machine learning models for classification, regression, and predictive analytics use cases, improving decision-making and operational efficiency. Performed feature engineering, data preprocessing, exploratory data analysis (EDA), and statistical analysis to enhance model performance and data quality. Built scalable data processing and ETL pipelines using PySpark and Apache Spark to support large-scale analytics and machine learning workflows. Designed and validated experiments using hypothesis testing, A/B testing, and statistical techniques to measure business impact and optimize product performance. Created interactive dashboards and visualizations using Power BI and Python to communicate key findings and performance metrics to business stakeholders. Collaborated with cross-functional tea