Principal Data Scientist – Health & AI

Commercial pharma is sitting on a measurement problem. Launch decisions, field force deployment, HCP engagement, pricing - most of the value moves before anyone knows what worked, and the standard playbooks weren't built for fragmented channels, privacy constraints, or the causal questions that actually matter to commercial leaders. And the ground keeps moving - AI is rewriting what "analytics" even means to a commercial org, and the regulatory and tech stack underneath it all is shifting faster than most teams can absorb.

Intellishore works at the sharp end of this. Our commercial pharma practice partners with global top-20 pharma pioneers on data and AI decisions that shape launches, portfolios, and commercial performance. We're hiring a Principal Data Scientist to lead the technical depth of this work — shaping methodology, owning delivery on our most demanding engagements, and building out how we deliver measurements, causal inference, and machine learning in the next generation of our offerings.

What you'll actually do

• Lead the data science workstream on senior client engagements - typically 1-2 concurrent projects, working directly with client executives and brand leadership.
• Set the technical bar on machine learning and forecasting across our commercial pharma portfolio and build the methods and templates that scale across the practice and into new segments.
• Mentor and grow a small team of data scientists and engineers. Team size: 10 today, growing to 30.
• Shape new offerings alongside our leadership - from scoping to pricing to the IP that underpins them.
• Represent Intellishore externally: Thought leadership, conferences, and senior client conversations where credibility matters.

Must-haves:

• 8+ years in data science, with meaningful time spent on machine learning and forecasting in commercial, marketing, or pricing contexts.
• Track record of leading senior client-facing engagements or business-critical internal programs - consulting, in-house commercial analytics, or both.
• Strong domain grounding in pharma, healthcare, or another regulated industry where commercial measurement is hard.

• Understanding MLOps at a level where you know what good looks like and can still get your hands dirty when it matters.
• Experience shaping or launching data/AI offerings, practices, or products.
• Danish is a plus, not a requirement. Our working language is English.

We're a boutique of ~100 people across Copenhagen and Zürich, and our commercial pharma stronghold is genuine - not a side bet. That means three things that matter at your level:

• Real mandate. You'll own the technical direction of a practice, not a single workstream within a larger machine. If you've wanted to shape how a firm approaches machine learning in healthcare, this is the seat.
• Concrete path. Practice Lead for ML in Commercial Pharma within 1–2 years; Director track over 2–4 years from hire. We'll map it to your ambitions in the first conversation.
• Compensation. We'll be direct about level, bonus structure, and the full package early in the process.

• Based in Copenhagen. Expect 3-5 days in the office or at the client site. Travel roughly 5% of weeks, primarily within Europe.
• You must have the right to work in Denmark at the time of application.

We read every application. If most of this resonates, but you don't tick every box, apply anyway — we'd rather have the conversation.

Reach out to Sofie Freund with questions: [email protected]

• +45 93 98 17 27. We interview on a rolling basis.