Sangameshwar Ryakala
Health Data Scientist & Analytics Professional
Transforming healthcare through data-driven insights. Specialized in health data analytics, machine learning applications in healthcare, and evidence-based research to improve patient outcomes and healthcare delivery systems.
About Me
Passionate health data scientist bridging the gap between healthcare and technology through innovative analytics solutions
Transforming Healthcare Through Data Science
Currently pursuing my Master's in Health Data Science at Saint Louis University, I bring a unique blend of pharmaceutical knowledge and data analytics expertise to healthcare challenges. My journey began with a Bachelor of Pharmacy, providing me with deep domain knowledge of healthcare systems and patient care.
With hands-on experience as a Health Data Analyst, I've successfully managed experimental datasets, implemented statistical workflows, and created visualizations that uncover critical insights about natural extracts and mental health effects. My work has consistently delivered measurable improvements, including a 20% reduction in analysis time through optimized Python workflows.
I'm passionate about leveraging AI and machine learning to solve real-world healthcare problems, from predicting hospital readmissions to understanding the impact of lifestyle factors on mental health. My goal is to make healthcare more efficient, accessible, and effective through data-driven insights.
Healthcare Analytics
Specialized in analyzing healthcare data to improve patient outcomes and operational efficiency
Machine Learning
Applied ML models including logistic regression and random forest for predictive healthcare analytics
Data Visualization
Expert in creating compelling visualizations using Tableau, Power BI, and Python libraries
Data Management
Proficient in SQL, FHIR/HL7 integration, and EHR data processing for healthcare systems
Professional Experience
A journey through healthcare analytics and data science roles where I've applied expertise to solve real-world health challenges
Health Data Analyst
SciTech
Hyderabad, India
Managed and validated structured experimental datasets, designed automated statistical workflows, and served as primary analytics point of contact for client meetings.
Key Achievements:
- Managed and validated structured experimental datasets using SQL and Excel, ensuring data integrity, regulatory compliance, and reporting readiness across client-driven research projects
- Designed and implemented automated statistical analysis workflows in Python (pandas, SciPy) to standardize extract efficacy evaluation, reducing analysis time by 20%
- Conducted advanced data visualization and trend analysis using Tableau and Matplotlib, translating complex analytical outputs into clear insights for technical and non-technical stakeholders
- Identified and communicated key correlations between natural extracts and antidepressant properties, directly informing data-driven research decisions and next-phase study planning
- Served as the primary analytics point of contact for client meetings, presenting findings, explaining methodologies, and aligning data insights with research and business objectives
- Collaborated cross-functionally with research, technical, and client stakeholders to ensure analytics solutions supported project timelines, decision-making, and measurable outcomes
Health Data Research Analyst Intern
Optum
Hyderabad, India
Analyzed and validated healthcare research articles and public health datasets against clinical guidelines, delivering evidence-based insights that improved data accuracy.
Key Achievements:
- Analyzed and validated healthcare research articles and public health datasets against clinical guidelines, delivering evidence-based insights that improved data accuracy and credibility of published healthcare content
- Translated complex medical research into data-backed insights and applied SEO performance metrics to optimize visibility, increasing engagement and reach of healthcare topics across digital platforms
Technical Skills
Comprehensive expertise in health data science, analytics, and modern technology stack for healthcare applications
Programming & Statistical Tools
pandas, SciPy, NumPy
MySQL, PostgreSQL
Statistical Analysis
Statistical Computing
Data Visualization
Advanced Dashboards
Business Intelligence
Python Visualization
Statistical Plots
Machine Learning & Analytics
Classification Models
Ensemble Methods
Model Interpretation
Time-to-Event
Unsupervised Learning
Cloud & Development
Cloud Computing
Microsoft Cloud
Version Control
GitHub Actions
Healthcare Data Management
Healthcare Standards
Electronic Health Records
Data Quality
Data Warehousing
Development Environment
IDE
R Development
Data Science
Package Management
Featured Projects
Showcase of healthcare data science projects demonstrating expertise in machine learning, analytics, and health informatics
Impact of Sleep Deprivation and Screen Time on Adolescent Mental Health
Performed comprehensive EDA and ML modeling using logistic regression, random forest, and clustering on Kaggle datasets to analyze the relationship between sleep patterns, screen time, and mental health outcomes in adolescents.
Key Achievements:
- Used SHAP analysis for feature importance interpretation
- Developed policy recommendations for mental health
- Identified key lifestyle factors affecting adolescent wellbeing
RemedyGenie
Innovative healthcare solution leveraging advanced technology to provide intelligent remedy recommendations and health guidance, combining data analytics with user-friendly interface for improved health outcomes.
Key Achievements:
- Developed intelligent remedy recommendation system
- Created user-friendly healthcare guidance interface
- Integrated advanced analytics for health insights
AI-driven Dataset Generator with Google Gemini API
Developed an innovative AI-powered dataset generation tool utilizing Google Gemini API to create synthetic healthcare datasets for research and analysis, enabling data scientists to work with realistic data while maintaining privacy.
Key Achievements:
- Integrated Google Gemini API for intelligent data generation
- Created synthetic datasets maintaining statistical properties
- Enabled privacy-preserving research methodologies
Predicting Hospital Readmissions Using Medicare Data
Built logistic regression and random forest models on 30K records to predict 30-day readmission risk, achieving AUC of 0.89 and identifying key comorbidities for intervention strategies.
Key Achievements:
- Achieved AUC score of 0.89 for readmission prediction
- Analyzed 30,000+ patient records
- Identified interventions reducing readmissions by 12%
Interactive Health Data Dashboards
Architected interactive health-data dashboards integrating PostgreSQL datasets with Looker Studio, enabling real-time monitoring of quality-of-care indicators and cutting reporting cycles in half.
Key Achievements:
- Reduced reporting cycles by 50%
- Enabled real-time quality-of-care monitoring
- Integrated multiple data sources seamlessly
Education & Certifications
Academic foundation and professional certifications in health data science and analytics
Education
Master of Science in Health Data Science
Saint Louis University
Jan 2024 - Dec 2025
Specialized in healthcare data analytics, machine learning applications, and evidence-based research to improve patient outcomes and healthcare delivery systems.
Bachelor of Pharmacy
Osmania University
June 2019 - June 2023
Comprehensive pharmaceutical education covering pharmacology, medicinal chemistry, pharmaceutical analysis, and clinical pharmacy practice.
Professional Certifications
Certified Health Data Analyst (CHDA)
AHIMA • 2023
Google Data Analytics Professional Certificate
Google • 2022
Microsoft Azure Data Scientist Associate
Microsoft • 2023