Career Profile
Accomplished analytics leader with 9+ years of experience in pharmaceutical and biotechnology sectors with proven track record in leading complex analytical teams and projects, integrating AI, and delivering high-impact evidence to cross-functional stakeholders. Architect of the analytics portfolio for metabolic and neurology therapeutic areas through the integrated evidence generation plans, study inception and design, and global support to the local teams for regulatory and reimbursement submissions. Committed to fostering a culture of continuous innovation and excellence to transform the healthcare landscape and improve patient lives globally.
Experiences
- Lead the conceptualization and design of research analytical projects in close collaboration with Medical, Market Access, and HEOR to understand the disease and patient journey, prepare product launches, and maximize the value of the products on the market.
- Manage external vendor/CRO partnerships and project timelines to ensure high-quality deliveries.
- Analysis of healthcare data, claims and EHR, to identify treatment patterns and clinical benefits across therapies.
- Reanalyze clinical trial datasets to investigate quality of life fluctuations, and subgroup analysis for several HTAs.
- Identification of underdiagnosed patient populations and quantifying market opportunities.
- Develop patient stratification models based on preceding comorbidities and longitudinal disease patterns to improve clinical phenotype prediction and population segmentation.
- Directed technical team members and led the end-to-end development of proteomics analysis platforms, focusing on automated feature extraction and synergy detection to advance precision medicine initiatives.
- Architected VariantSpark, a cloud-based distributed ML tool for analyzing complex epistatic interactions; successfully developed polygenic risk scores for Cardiovascular (CV) risk, translating genomic complexity into actionable clinical predictors.
- Lead a multi-modal data generation project to create high-fidelity synthetic datasets encompassing genetics, biochemistry, imaging (2D/3D), and clinical text.
- Got granted a patent and lead the commercialization strategy for federated data generation.
- Led the developed of Deep Learning (CNN) models for the automated grading of diabetic retinopathy, significantly improving lesion identification in large-scale biomedical imaging datasets.
- Performed longitudinal patient journey mapping using large-scale EHR/EMR registries to stratify populations and differentiate complex disease states like Alzheimer’s vs. vascular dementia.
- Executed advanced time-to-event mortality analyses across Danish national databases, identifying causal drivers.
- Authored technical reports and collaborated on research initiatives that translated complex temporal data into actionable clinical insights.
- Developed a tool to analyze protein sequences to devise critical amino acid pairs correlations within the same protein family. Those pairs were regarded as critically relevant for the protein structure and function and thus a key element to identify homologs.
- JavaScript implementation of a webpage for protein alignment visualization (alignmentviewer.org).
- Provided comprehensive analysis for pharmaceutical and insurance clients utilizing PostgreSQL, Python, and R.
- Optimized patient clustering models for Multiple Sclerosis (MS) based on longitudinal treatment history to improve understanding of disease progression.
- Engineered a high-performance patient similarity scoring algorithm capable of processing and analyzing records for millions of individuals in a production environment.
Publications
This is a selection of my publications, for a more detailed list you can visit my google scholar profile.
Scientific reports, 2025
Nature communications, 2020
Bioinformatics, 2025
Scientific Reports, 2021