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iLOF is an AI-powered precision medicine platform recognized by CB Insights and Financial Times as one of the most promising digital health companies globally. The company uses proprietary optical fingerprinting to enable personalized patient screening and stratification, with current focus on Alzheimer's diagnostics alongside verticals in digestive cancer, stroke, and infectious diseases.
You will manage iLOF's Data Science team day-to-day, setting clear expectations, conducting 1:1s, providing regular feedback, and supporting team development and performance management. Your core responsibilities include:
**Team Leadership & Delivery**: Transform priorities from scientific and executive leadership into sprint and project plans. Allocate people, manage dependencies, and track milestones. Serve as the first point of call for prioritization questions, escalating trade-offs early and keeping the team focused on what matters most. Keep projects on track from scoping through validation and handover, flagging risks and slippage early.
**Technical Standards & Quality**: Ensure software is built properly through version control, code review, testing, reproducible pipelines, and documentation. Work closely with the software team to bridge the gap between development and production-ready requirements, moving prototypes and models into robust, validated, and deployable products. Bring structure to team workflows through lightweight processes, clear definitions of done, and standards for analysis review and model validation.
**Cross-Functional Collaboration**: Work across Biology, Photonics, Engineering, and Clinical teams to keep data acquisition, analysis, and product needs aligned.
**Team Development & AI Strategy**: Train and upskill the team by identifying skill gaps, running structured training, pair programming, and code/analysis reviews. Bring in external courses or experts as needed. Lead AI tools strategy and implementation: set strategy for how the team uses AI tools (coding assistants, LLMs and agents, AutoML, experiment tooling), select and roll out tools, define guidelines for safe and rigorous use including data protection and validation of AI-generated work, measure productivity and quality impact, and share learnings across the company.
**Reporting & Hiring**: Report progress, risks, and decisions clearly to leadership. Contribute to hiring and onboarding.
**Requirements**
Must have:
- Several years of industry experience leading data science, machine learning, or engineering teams to delivery (managing people, not only projects)
- Degree (MSc or PhD preferred) in a quantitative field such as electrical engineering, signal processing, physics, applied mathematics, statistics, or computer science
- Hands-on background in data science or ML, with working understanding of modeling, validation, and pitfalls of small or noisy datasets
- Strong software engineering practice: ability to set and enforce standards for code quality, testing, and reproducibility
- Hands-on experience leading adoption of AI tools in a technical team: choosing tools, rolling them out, setting usage guidelines, and showing measurable gains
- Track record of developing people: designing training, coaching, and mentoring that visibly raised team skills
- Proven project and delivery management: planning, prioritization, risk management, and stakeholder reporting
- Experience running Agile delivery (Scrum or Kanban): sprint planning, backlog management, stand-ups, and retrospectives
- Hands-on proficiency in Python, SQL, and Git, and practical experience building with agentic AI (LLM agents, tool use, multi-step automated workflows)
- Excellent communication in English with technical and non-technical colleagues
Strong plus:
- Experience with signal or sensor data (signal processing, spectroscopy, time series, instrumentation)
- Experience in a scale-up or start-up with an AI or deep-tech component
- Work experience on clinically certified or regulated products (CE-IVD, FDA-cleared devices, software as a medical device), or wider exposure to medtech and diagnostics
