Building predictive models for bioprocess optimization at Solid Biosciences. Specialized in upstream analytics for gene therapy manufacturing and clinical trial data analysis.
Bridging data science and biotechnology for breakthrough discoveries
Data scientist specializing in bioprocess optimization and gene therapy analytics. I develop machine learning models to enhance manufacturing efficiency and support clinical development of life-saving treatments.
At Solid Biosciences, I focus on upstream process analytics for SGT-003, building predictive models that optimize cell culture conditions and improve vector yield. My work directly impacts the development of treatments for Duchenne muscular dystrophy and other rare genetic diseases.
Let's ConnectEducation and experience in data science and biotechnology
GPA: 3.8/4.0 | Focus: Biotech Analytics & Predictive Modeling
View Detailed Coursework
GPA: 3.6/4.0 | Specialized in environmental health data analysis and biostatistics
• Engineering automated data pipelines for bioreactor analytics, processing real-time sensor data from capacitance probes and dissolved oxygen monitors to optimize gene therapy vector production
• Developing machine learning models for cell growth prediction and yield optimization, achieving improvement in batch-to-batch consistency for SGT-003 manufacturing
• Building interactive dashboards using Python and Tableau to monitor critical process parameters, enabling rapid decision-making for upstream bioprocess development teams
• Implementing statistical process control methods and multivariate analysis to identify process deviations early and reducing manufacturing failures
• Built predictive models using logistic regression and random forests to forecast patient admission patterns, improving resource allocation accuracy by 15%
• Automated reporting workflows with Python and SQL, reducing manual analysis time by 35%
• Analyzed epidemiological datasets using R and SQL to identify seasonal disease patterns
• Created interactive visualizations connecting environmental factors with health outcomes
Professional credentials and academic honors
Specialized skills in biotech data science and analytics
Data science solutions across healthcare and biotechnology
Built predictive models to identify at-risk students and optimize intervention strategies. Developed automated dashboards for real-time monitoring of attendance patterns and academic performance.
Developed ensemble machine learning models for early diabetes detection using clinical biomarkers. Achieved 94% accuracy with feature importance analysis for clinical interpretation.
Created comprehensive BI solution for strategic decision-making. Built ETL pipelines and real-time dashboards that improved operational efficiency and data-driven insights across departments.
Ready to discuss data science opportunities in biotechnology
Open to opportunities in biotech data science, machine learning engineering, and analytics roles. Let's discuss how data can drive your next breakthrough.