At Combyn Health Care, we are building technology that makes preventive medicine faster, smarter, and more accessible. Our flagship product, BioCore Loop, is a physical‑meets‑digital screening system that captures multi‑modal health data in minutes — including ECG signals, segmental bioelectrical impedance data, weight metrics, and 3D body measurements. The goal is simple but ambitious: detect long‑term cardiovascular and metabolic risks earlier, more accurately, and at scale. We are a young, fast‑moving team with a flat structure, high ownership, and very little tolerance for corporate theater. No endless approval loops. No rigid department walls. No “that’s not my job” mindset. We build, test, learn, improve — and move. The role
Lead Data Scientist – Medical Analytics to take ownership of our cloud‑based analytics layer. BioCore Loop streams high‑fidelity raw sensor data into the cloud. Your mission is to turn that raw biological data into meaningful, clinically relevant insight. You will work with ECG curves, impedance spectroscopy signals, body composition data, 3D body scans, and historical medical records — then design the models, pipelines, and analytical architecture needed to transform this data into predictive health metrics. This is not a role for someone who wants to maintain a dashboard someone else designed. This is a role for someone who wants to shape the analytical brain of a medical technology platform from the ground up. What you’ll work on
1. Cloud‑based biomedical signal fusion
— process and combine raw ECG and BIA signals in the cloud, building algorithms that connect different physiological data streams into stronger cardiovascular and metabolic risk indicators. 2. Raw data exploration at scale
— work directly with electrical cardiac signals, impedance waves, weight and body composition data, and 3D Time‑of‑Flight camera point clouds to extract as much meaningful physiological signal as possible. 3. Scalable analytics architecture
— design flexible cloud processing systems that can ingest, normalize, analyze, and evolve with our current and future data sources. 4. Medical data integration
— help merge high‑frequency sensor streams with historical medical records from doctors and legacy health systems, turning fragmented data into a coherent longitudinal health picture. 5. Close collaboration with engineering + medical team
— work directly with hardware, firmware, backend, and product people to influence how data is captured, streamed, stored, and processed — from sensor to cloud to insight. What we’re looking for
Strong Python skills:
highly comfortable with Python and scientific computing tools such as Pandas, NumPy, SciPy, Scikit‑learn, and related libraries. Production analytics experience:
built data or ML pipelines that run outside of notebooks and can survive real‑world usage. Cloud data architecture experience:
know how to think about scalable data ingestion, processing, storage, and deployment in cloud environments. Biomedical signal processing expertise:
hands‑on experience with time‑series or biomedical signals — ideally ECG processing, filtering, QRS detection, HRV analysis, impedance spectroscopy, or related physiological signal domains. A research‑driven builder mindset:
can look at messy data, form a hypothesis, build a prototype, validate it, and iterate quickly. Strong analytical foundations:
background may be in data science, biomedical engineering, physics, mathematics, computer science, or something equivalent. We care more about how you think than the title of your degree. Bonus: 3D / spatial data experience:
experience with point clouds, 3D body scans, computer vision, or Time‑of‑Flight camera data is a strong plus. Language skills:
fluent English is important for our international team. German is helpful, especially for local engineering and medical collaboration, but not required. Who will thrive here
You want real ownership instead of narrow ticket work. You like working close to hardware, data, and product at the same time. You prefer fast iteration over long internal politics. You are excited by raw, messy, high‑value biological data. You want your algorithms to power a real physical medical device ecosystem. You enjoy building things where no one has written the perfect specification yet. You may not enjoy this role if you need a fully defined corporate structure, large support departments, or a polished 50‑page requirements document before you start experimenting. What we offer
Real autonomy:
own major decisions around the data science roadmap, signal processing strategy, and cloud analytics architecture. A meaningful product:
directly influence a medical screening system designed to detect health risks earlier and improve preventive care. A young, highly motivated team:
work with people who care deeply about building, learning, and moving fast. Flexibility:
work from our Graz office, from home, or hybrid — what matters most is quality, momentum, and clear collaboration. Competitive compensation:
For legal reasons, we state the Austrian collective agreement baseline of €4,500 gross/month. For the right senior expertise, we are fully prepared to pay significantly above this level.
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