Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

I am Manish Pareek, a PhD-qualified MLOps Engineer with over seven years of experience across pharmaceutical CRO environments, data engineering, and production ML deployment. I have delivered end-to-end ML systems for credit risk, insurance pricing, churn, and computer vision, leveraging MLflow for experiment tracking and model registry, FastAPI deployment, and CI/CD automation. I thrive in fast-paced, cross-sector agile settings and have consulting experience delivering ML systems for financial services, insurance, and telecom clients. I am comfortable navigating regulated environments with GLP/SOP practices and am proficient in Python, cloud platforms (Azure, AWS), and modern ML tooling.…I am Manish Pareek, a PhD-qualified MLOps Engineer with over seven years of experience across pharmaceutical CRO environments, data engineering, and production ML deployment. I have delivered end-to-end ML systems for credit risk, insurance pricing, churn, and computer vision, leveraging MLflow for experiment tracking and model registry, FastAPI deployment, and CI/CD automation. I thrive in fast-paced, cross-sector agile settings and have consulting experience delivering ML systems for financial services, insurance, and telecom clients. I am comfortable navigating regulated environments with GLP/SOP practices and am proficient in Python, cloud platforms (Azure, AWS), and modern ML tooling.

Manish Pareek

AI Engineer, Data Scientist, DevOps Developer





I am Manish Pareek, a PhD-qualified MLOps Engineer with over seven years of experience across pharmaceutical CRO environments, data engineering, and production ML deployment. I have delivered end-to-end ML systems for credit risk, insurance pricing, churn, and computer vision, leveraging MLflow for experiment tracking and model registry, FastAPI deployment, and CI/CD automation. I thrive in fast-paced, cross-sector agile settings and have consulting experience delivering ML systems for financial services, insurance, and telecom clients. I am comfortable navigating regulated environments with GLP/SOP practices and am proficient in Python, cloud platforms (Azure, AWS), and modern ML tooling.…I am Manish Pareek, a PhD-qualified MLOps Engineer with over seven years of experience across pharmaceutical CRO environments, data engineering, and production ML deployment. I have delivered end-to-end ML systems for credit risk, insurance pricing, churn, and computer vision, leveraging MLflow for experiment tracking and model registry, FastAPI deployment, and CI/CD automation. I thrive in fast-paced, cross-sector agile settings and have consulting experience delivering ML systems for financial services, insurance, and telecom clients. I am comfortable navigating regulated environments with GLP/SOP practices and am proficient in Python, cloud platforms (Azure, AWS), and modern ML tooling.

Available to hire

I am Manish Pareek, a PhD-qualified MLOps Engineer with over seven years of experience across pharmaceutical CRO environments, data engineering, and production ML deployment. I have delivered end-to-end ML systems for credit risk, insurance pricing, churn, and computer vision, leveraging MLflow for experiment tracking and model registry, FastAPI deployment, and CI/CD automation. I thrive in fast-paced, cross-sector agile settings and have consulting experience delivering ML systems for financial services, insurance, and telecom clients. I am comfortable navigating regulated environments with GLP/SOP practices and am proficient in Python, cloud platforms (Azure, AWS), and modern ML tooling.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Work Experience

Data Scientist/MLOps Engineer at Pragmaa Pvt Ltd

June 1, 2025 - Present

Built and deployed an end-to-end credit risk classification system with a production-grade preprocessing pipeline ensuring feature parity between training and inference to prevent data leakage and drift; achieved 94% recall through structured experiments and cost-based threshold optimization. Containerised the application with Docker and deployed via FastAPI, and established CI/CD pipelines using GitHub Actions to automate testing, training, and deployment, with model monitoring using PSI/CSI metrics to trigger automated retraining. Designed and deployed a health insurance premium prediction system using a hybrid logistic regression/XGBoost approach with medical risk normalization, achieving ~98% accuracy and delivered as a modular Streamlit app. Developed a customer churn prediction model for online retail, optimizing decision thresholds for business costs and improving retention. Built a computer vision-based damage-detection system for insurance claims, training a CNN on vehicle ima

Senior Data Specialist / Scientific Analytics Lead at C4X Discovery

October 1, 2023 - February 28, 2025

Led end-to-end data delivery across six concurrent drug discovery programmes, owning requirements capture, validation, and reporting to ensure audit-ready outputs under GLP and SOP compliance. Built a binding energy prediction model from >50 features and >10,000 datapoints, achieving 72% accuracy to aid candidate design. Built Python and SQL data pipelines integrating operational, scientific, and financial datasets with ETL, cleansing, deduplication, and multi-stage validation to reduce downstream data quality issues and external costs. Designed and implemented a KPI performance framework with 15+ metrics translated into Power BI dashboards (DAX, star schema) for real-time leadership visibility. Served as primary data liaison between C4X and CRO partners, translating objectives into structured data deliverables for 16 chemists across six programmes. Led a process improvement initiative reducing a key workflow from 10 steps to 6, delivering ~40% efficiency gain.

Senior Scientist at Sygnature Discovery

October 1, 2019 - October 31, 2023

Designed and maintained structured reporting frameworks for 10+ external pharmaceutical clients and internal leadership, integrating high-dimensional datasets from LIMS, performing data interrogation, QC, and anomaly detection to ensure outputs were accurate, consistent, and timely. Developed and optimized SQL queries for data extraction, cross-dataset analysis, and performance reporting across large relational databases. Supported migration from legacy ELN to cloud-based ELN as a validation expert, validating the migration through SQL-based checks at each step.

Postdoctoral Researcher at University of Paris-Sud

April 1, 2017 - September 30, 2018

Applied advanced statistical and quantitative methods to complex biomedical datasets, producing peer-reviewed publications and presenting findings to academic and industry partners, establishing rigorous analytical foundations and domain expertise underpinning subsequent data science and ML engineering work.