Data Scientist (AI/ML) with 5+ Years Experience

Aakash Sunil Chaudhari

Data Scientist (AI/ML)

USA +1-216-***-**** Email: *******************@*****.*** LinkedIn SUMMARY

Results driven Data Scientist with 5+ years of experience designing scalable machine learning solutions, predictive analytics models, and AI driven platforms across healthcare and enterprise environments. Experienced in building end to end data science pipelines using Python, SQL, cloud ML platforms, and advanced statistical modeling techniques to drive measurable business outcomes. Proven track record of improving model accuracy, optimizing large scale datasets, and deploying production ready AI solutions that enhanced operational efficiency by over 30%. Strong expertise in integrating AI/ML into real world business workflows, collaborating with cross functional stakeholders, and delivering analytics driven insights aligned with USA healthcare and enterprise standards. PROFESSIONAL EXPERIENCE

Data Scientist (AI/ML) Centene Corporation USA June 2025 – Present

Designed predictive models using Python, PySpark, and AWS SageMaker to analyze 40M+ healthcare records, improving risk prediction accuracy by 28% and reducing manual data preparation time by 35% through automated feature engineering.

Built end to end ML pipelines integrating SQL extraction, preprocessing, and model deployment workflows, enabling faster analytics delivery and improving decision making efficiency by over 30% across clinical teams.

Developed NLP solutions using transformer based models to analyze unstructured clinical text, improving classification accuracy by 32% and reducing manual review effort through automated AI driven insights.

Collaborated with data engineering teams to deploy scalable AI solutions using Databricks and Azure ML, improving production stability and reducing model retraining cycles by 25%.

Created Tableau and Power BI dashboards to visualize predictive outputs and healthcare KPIs, improving executive reporting visibility and reducing manual reporting effort by 40%.

Implemented model monitoring using MLflow and cloud logging tools to track performance and detect drift, improving long term model reliability by 20%.

Performed statistical analysis and feature engineering using Python and R to identify cost drivers in healthcare datasets, supporting initiatives that improved operational efficiency by 22%.

Partnered with Agile teams to translate business needs into AI solutions, validating model performance and ensuring HIPAA compliant analytics delivery.

Optimized SQL queries and data transformations, improving dataset preparation speed by 30% and accelerating model experimentation cycles.

Data Scientist (AI/ML) Mphasis India Feb 2019 – July 2023

Built machine learning models using Python and XGBoost on datasets exceeding 20M records, improving customer segmentation accuracy by 26% and enabling data driven business strategies.

Designed ETL workflows using SQL and PySpark to integrate multi source enterprise data, improving data quality by 35% and reducing manual preprocessing effort.

Developed predictive analytics models for churn analysis and demand forecasting, increasing forecast accuracy by 24% and supporting operational planning initiatives.

Implemented NLP pipelines for document classification using deep learning frameworks, reducing manual analysis workload by 30% across analytics projects.

Created Tableau and Power BI dashboards to present model insights and KPI metrics, improving stakeholder visibility into performance trends.

Deployed machine learning models on AWS using containerization and CI/CD pipelines, improving deployment efficiency by 25% and enabling scalable production delivery.

Applied feature engineering and model evaluation techniques to improve precision and recall metrics by 18% across multiple projects.

Collaborated with business analysts and product teams to convert requirements into scalable AI solutions, improving workflow efficiency by 20%.

Optimized SQL based data models and transformations, improving processing performance and accelerating model training cycles. TECHNICAL SKILLS

Programming & Data Science: Python, R, SQL, Pandas, NumPy, SciPy

Machine Learning Algorithms: Regression, Random Forest, XGBoost, Gradient Boosting, SVM, Clustering

Deep Learning & NLP: TensorFlow, PyTorch, NLP Pipelines, Transformer Models, Text Analytics

AI Integration & Generative AI: LLM Integration, Prompt Engineering, AI Automation Workflows

Data Engineering & Processing: PySpark, ETL Pipelines, Data Cleaning, Feature Engineering

Visualization & BI Tools: Tableau, Power BI, Matplotlib, Seaborn

Cloud Platforms & ML Services: AWS SageMaker, Azure ML, Databricks

MLOps & Deployment: Docker, CI/CD, Model Monitoring, MLflow

Databases & Warehousing: Snowflake, PostgreSQL, MySQL, Data Modeling

Statistical Analysis: Hypothesis Testing, Forecasting Models, Predictive Analytics

Agile & Collaboration Tools: Jira, Confluence, Agile Scrum Methodologies

Data Governance & Compliance: HIPAA, Data Privacy Standards, Secure Data Handling EDUCATION

Master of Information Systems Cleveland State University, Cleveland, Ohio, USA Aug 2023 – May 2025 Bachelor of Engineering In Electronics and telecommunication MIT College of Engineering, Aurangabad, India Aug 2014 – Dec 2018

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