Senior Machine Learning Engineer (Medical Digital Twin)

🚀 Senior Digital Twin Expert / Applied ML Engineer (Freelance)Location: Remote in Europe / EU (Occasional travel to Munich) Rate: Very Competitive Language: English speaking Start Date: ASAP Duration: Initial 4 Months (Project-based, potential extension to end of year)🌟 The CompanyOur client is a Munich-based digital health company dedicated to improving the lives of people with rare diseases. Backed by a major pharmaceutical corporation, their products are developed collaboratively with patients and healthcare professionals.They already have a strong internal data engineering and data science team, but they are looking to build an entirely new vertical and capability: Digital Twins. They need a hands-on external expert to come in, build the first successful Proof of Concept (PoC), and help transfer this knowledge to their internal team.💡 The ProjectAs a Senior Digital Twin Expert, you will lead the design and hands-on implementation of a Digital Twin PoC using real-world clinical and digital health data.You will not be starting from scratch with messy data. The internal data team has already pipelined longitudinal, time-resolved data (spanning up to 6 years across thousands of patients with rare diseases like Haemophilia) into Snowflake/AWS. You will be provided a secure, sandboxed environment to work in.Your specific goal is to build working Python code/scripts that simulate different drugs' impact on disease progression (e.g., predicting bleeding events). This is a high-visibility, 0-to-1 project. A successful PoC will prove the value to their investors and set the foundation for future monetization and regulatory clinical trial use.🎯 ResponsibilitiesBuild the PoC: Design and implement Digital Twin models based on real-world digital health and clinical study data.Hands-on Modeling: Apply statistical, ML-based, or hybrid modeling approaches to generate models that resemble real clinical behavior (e.g., simulating drug impact on rare diseases).Feature Engineering: Perform advanced data engineering and feature modeling to prepare complex healthcare datasets for simulation.Knowledge Transfer: Collaborate closely with the internal data team to transfer knowledge, advise on toolchains, and enable internal capability building.Refine the Vision: Challenge assumptions, act as the domain expert, and help the leadership team refine the use cases for practical, commercial outcomes.💻 Tech Stack & EnvironmentLanguage: Python, but they are open to experience with any stack. Infrastructure: AWS (Nice to have).Data Warehouse: Snowflake (Nice to have).Modeling: Technology-agnostic. You choose the right ML/statistical frameworks to get the job done.🛠️ Your ExperienceSeniority: 5+ years of experience in the Data Science / Machine Learning realm.Digital Twin Mastery: 3+ years of specific, operational experience creating Digital Twins, patient-level simulations, or synthetic data in the Medical/Pharma domain.Operational vs. Academic: You must have senior-level experience with at least one operationally implemented Digital Twin project (purely academic/research backgrounds will not be a fit).Clinical Data: Strong understanding of healthcare data structures, variability, and limitations (e.g., interventional, observational, Real-World Evidence).🎁 Benefits of this ContractHigh Impact / 0-to-1: You are building a brand new technical vertical for a highly funded scale-up.Clean Data: You aren't wasting 3 months cleaning CSVs; the data is pipelined and ready to model.Fast Process: Streamlined 2-step interview process with immediate decision-making.📝 Interview Process Intro Call: Experience, project alignment, and culture check with Head of Technology.Technical Deep Dive: A discussion with CEO and a Senior Data Engineer. This will focus on your practical approach to Pharma/MedTech data, how you build Digital Twins, and your understanding of good data practices.Offer: Immediate decision and Statement of Work (SOW).