Data Science Expert and AI Strategist

I specialize in designing and deploying scalable machine learning solutions for organizations aiming to boost operational efficiency and profitability. My expertise spans from strategic consulting to hands-on MLOps, leveraging modern ML frameworks, Docker, and AWS to deliver automated, cloud-native pipelines that drive tangible impact.

• Strategy consulting and requirements gathering.
• Coaching and upskilling team members.

Technologies: Python, CI/CD, AWS, Docker, SQL, genAI

Digital Execution Strategy Development

• Led an 8-person global cross-functional team, embedding MLOps best practices to streamline AI-driven cloud deployment and operational execution.

• Developed end-to-end cloud-based ML workflows, aligning business objectives with technical strategy to reduce time-to-market for digital transformation initiatives.

• Established processes for empowered decision-making, driving agile execution across AI product development.

• Upskilled team on design thinking methodologies, AI strategy, and qualitative user research.

• Team leadership and strategic planning.

• Cloud-native AI development and agile methodologies.

Technologies: Jira, Confluence, Mural, AWS, CI/CD

Digital Transformation in Medical Writing

• Conducted process mapping and qualitative analysis to define AI-driven business use cases.

• Led generative AI adoption by medical writers and conducted PoCs on LLM-driven document generation, redaction, and translation.

• Performed market scouting and vendor analysis, streamlining RfP processes.

• Technical leadership and cross-functional facilitation.

• genAI and Azure Cognitive Services technologies.

Lay Document Generation Using RAG System

• Advised Data Scientists and Medical Writers on LLM prompt engineering and AI-powered document structuring to enhance faster content generation.

• Co-deployed a cloud-native prototype using Streamlit for AI-assisted content creation for the lay language protocol.

• Technical leadership and product innovation.

• RAG architecture implementation.

Technologies: Python, Llama Index, Azure Cognitive Services, OpenShift, Jenkins

Product Owner of Analytics Landing Page

• Served as Product Owner for an AI-driven analytics dashboard integrating recommendation systems and LLM-based cognitive search for real-time insights.

• Defined product vision, roadmap, and backlog grooming.

• Managed dependencies and aligned stakeholders for enterprise-wide data-driven decision-making.

• Product ownership and stakeholder management.

• AI model deployment and cloud-based API integration.

Technologies: LLMs, Azure Cognitive Services, AWS, Jira, Confluence, Git

Development of Bioinformatics Pipelines for Genome Assembly Algorithms

• Led a cross-functional team to develop bioinformatics pipelines on AWS cloud services.
• Focused on creating ultra-fast genome assembly algorithms.
• Utilized AWS CDK for infrastructure management.

Technologies: AWS Batch, AWS IAM, AWS Step Functions, AWS ECS, AWS CodePipeline, Python, Docker

Clinical Data Catalogue

• Developed ETL processes in Python to produce a clinical data catalogue integrating historical and in-house data.
• Implemented semantic search capabilities using advanced NLP pipelines.

Technologies: Python, Jupyter Notebooks, Docker, SPARQL, SQL, Stardog, PostgreSQL

Interdisciplinary Hackathon Creating Gamified NLP Annotation in a Web App

• Led a 2-day hackathon to gamify NLP annotation for biomedical researchers.
• Developed a game to validate NLP entity linking models.

Conceptualization of Bespoke Knowledge Management System Including PoC

• Conducted qualitative user research and led design sprints to produce advanced NLP-enhanced prototypes.

Technologies: Python, TensorFlow, Elasticsearch

Curation and Reporting of High-Dimensional Datasets

• Collaborated across departments to collect and analyze high-dimensional datasets from an observational clinical trial in hepatocellular carcinoma patients.
• Created interactive reports for treating physicians.

Technologies: Python, DICOM, TensorFlow, Seaborn

Clinical Reporting Strategy of Genetic Variations

• Created genetic variation reports to support oncological decision-making.

Technologies: REST API, Docker

Using Parallel Coordinates to Visualize Neural Networks

• Developed methods for neural network architecture visualization, aiding hyper-parameter estimation.

Technologies: TensorFlow