# 🌟 Success Factors for Biotech DS Teams Eric J. Ma, Sc.D. --- ## 🙋‍♂️ About Me - **Name:** Eric J. Ma - **Role:** Principal Data Scientist at Moderna - **Website:** [ericmjl.github.io](https://ericmjl.github.io/) --- ## Today's slides [ericmjl.github.io/ds-team-success-factors](https://ericmjl.github.io/ds-team-success-factors/) --- ## 🎯 Today's Focus --- Q1: What does it take for a data science team to successfully deliver long-lasting impact through data products? --- Q2: How do we do that in a biotech research setting? --- ## 🗝️ Four Key Ideas 1. A framework for bounding work 2. Clarity on high-value use cases 3. Technical and interpersonal skillsets 4. Necessary surrounding context --- ## 💭 Philosophy - Aim for lasting solutions beyond project duration. - Focus on building solutions that serve long-term. --- ## 📚 Idea 1: Framework @ Moderna DSAI - 3 rows: mRNA, Proteins, LNPs - 3 columns: AI library design, computer vision, probabilistic models + custom algorithms --- ## ❌ What we don't do - Bioinformatics - Computational chemistry - Protein structure modelling Clarity is key for collaboration. --- ## ❓ What does your team do and not do? - Clear lines of division - Dynamic range when necessary --- ## 🔍 Idea 2: Clarity on High-Value Use Cases - Highest value takes priority. - Two definitions of value: - Trade between a data scientist's time and another team's time. - New capabilities unlocked and their expected value. --- ## 🌟 Examples - Automated chromatography analysis - Predictive models for AI library design - Quantitative image analysis --- ## 🧵 Threads - Save time - Unlock new capabilities --- ## 🛠️ Idea 3: Technical and Interpersonal Skillsets - [Hiring and Interviewing Data Scientists](https://ericmjl.github.io/essays-on-data-science/people-skills/hiring/#scientific-knowledge) - People skills - Communication skills - Scientific domain knowledge - Software development skills - Modeling skills --- ## 🧠 Modeling Skills Going beyond off-the-shelf models: - Mechanistic - Probabilistic - Deep learning --- ## 💻 Software Development Skills - Refactoring - Documentation - Testing - Versioning > Projects live long when they are built like well-designed software. --- ## 🔬 Scientific Domain Knowledge - Language, vocabulary, vernacular - Understanding of the scientific process > A nuanced understanding of our colleagues' work builds trust and credibility! --- ## 🗣️ Communication Skills - Clear, concise, and effective - Upwards, downwards, and sideways --- ## 👥 People Skills - Opinionated and empathetic - Bridge builder - Drives towards clarity - Resilient under pressure --- ## 🌐 Idea 4: Necessary Surrounding Context - Integration into research processes. - Robust technology stack for longevity. --- ## 📖 Story 1: ML for Protein Engineering --- ## 🐁 Story 2: Mouse Motion Analysis --- ## 💻 Story 3: Computational Design Workflow --- ## 🚀 Moderna DSAI Deliverables - Python packages - Cloud-skinned CLI tools - AI library designs > Product-orientation gives us scale beyond service-orientation. --- ## 🛠️ Technical Infrastructure - Standardized project scaffold - Single deployment endpoint --- ## 🧐 Radical Clarity 1. What we do and don't do 2. High-value use cases 3. Technical and interpersonal skillsets 4. Necessary surrounding context --- ## ⭐️ Thank you