Nitish Kumar Manthri

Data Scientist | Data Analyst
San Jose, US.

About

Highly analytical and results-driven Data Scientist with a Master's in Computer Science, specializing in developing and deploying scalable machine learning models, ETL pipelines, and interactive dashboards. Proven ability to translate complex data into actionable insights, driving significant improvements in operational efficiency, fraud detection, and business intelligence within healthcare and finance sectors. Eager to leverage expertise in Python, SQL, AWS, and advanced analytics to solve challenging data problems and contribute to data-driven decision-making.

Work

Syneos Health
|

Data Scientist

Charlotte, NC, US

Summary

Led advanced analytics initiatives to transform healthcare data into actionable insights, improving operational efficiency and executive decision-making.

Highlights

Architected production-ready Streamlit dashboards for healthcare KPI monitoring, improving executive decision-making efficiency by 35% by automating reporting pipelines and replacing manual Excel workflows.

Designed and deployed scalable Python analytics applications using Flask/FastAPI on AWS (S3, Redshift, EMR), processing fragmented healthcare data with Docker containerization and GitHub Actions CI/CD pipelines.

Implemented ML-powered anomaly detection workflows and real-time alerting systems, reducing data processing time by 58% (from 12 to under 5 hours) while maintaining 99.5% system uptime.

Crafted interactive Power BI and Plotly visualizations with automated monitoring for data quality and latency, improving care satisfaction insights by 18% and supporting daily operational reviews.

Orchestrated complex ETL workflows using Airflow and dbt models, eliminating deployment bottlenecks and reducing release cycles from weeks to days.

Metafin Inc.
|

Data Analyst

Hyderabad, Telangana, India

Summary

Analyzed financial data and developed predictive models to enhance fraud detection, optimize marketing spend, and improve business intelligence.

Highlights

Shipped production fraud detection Streamlit applications utilizing Isolation Forest models on Databricks, achieving 97% precision and preventing multi-million-dollar losses through real-time dashboard monitoring.

Engineered automated analytics pipelines with Kafka streaming and Spark, enabling instant anomaly alerts for high-risk financial activities and supporting rapid rate reviews for revenue managers.

Developed ARIMA forecasting models and A/B testing frameworks in Python, optimizing marketing spend decisions and improving campaign ROI by 25%.

Constructed performant SQL queries and window functions on Snowflake/MongoDB, consolidating siloed ETL processes and reducing system latency by 40% for near real-time business intelligence.

Established CI/CD best practices using Docker and automated testing, ensuring high code quality and documentation standards across the analytics stack.

Education

University of Memphis
Memphis, TN, United States of America

Master of Science

Computer Science

Grade: 3.8/4.0

Sreyas Institute of Engineering and Technology
Hyderabad, Telangana, India

Bachelor of Technology

Computer Science

Grade: 3.65/4.0

Languages

English

Skills

Programming Languages

Python, SQL, Scala, Java.

Analytics Applications

Streamlit, Flask, Fast API, Dash, Panel.

Cloud & Data Platforms

AWS (S3, Redshift, EMR, EC2), Snowflake, Databricks, Apache Spark, PySpark, Kafka.

Data Visualization

Plotly, Matplotlib, Altair, Power BI, Tableau, Seaborn.

Databases

Redshift, Snowflake, MySQL, MongoDB, Cassandra.

ETL & Orchestration

Airflow, Prefect, dbt, SSIS, Data Vault, Dimensional Modeling.

Machine Learning & Analytics

Scikit-learn, XGBoost, BERT, TensorFlow, ARIMA, A/B Testing, Anomaly Detection.

DevOps & CI/CD

Docker, Kubernetes, Git, GitHub Actions, ECS, Infrastructure as Code.

Methodologies

Agile/Scrum, Code Quality, Testing, Documentation.

Projects

Airline Revenue Analytics Platform

Summary

Developed an end-to-end analytics application for airline revenue and occupancy rate analysis, integrating a Streamlit frontend with SQL/Python backend.

Advanced Cardiac Disease Risk Prediction Platform

Summary

Developed an ML-powered Streamlit application for cardiac risk assessment, leveraging advanced machine learning techniques.

BunnyBuddy: E-commerce Analytics Platform

Summary

Developed a full-stack e-commerce analytics platform with React.js frontend and Node.js microservices, implementing event-driven architecture.