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Applied ML Engineer/Data Scientist

Grape HealthZürich, SwitzerlandFull-timeSalary not listed · Typical pay in SwitzerlandPosted Nov 5, 2026

Grape Health is hiring for the position of Applied ML Engineer/Data Scientist in Zürich, Switzerland. It is listed as a full-time position with hybrid working.

Written by Dev Global Jobs

DGJ summary of this job

Our own short read of this listing, built only from the facts it gives. The employer’s original text follows further down.

Grape Health is hiring for the position of Applied ML Engineer/Data Scientist in Zürich, Switzerland. It is listed as a full-time position with hybrid working.

Reading the advert, the employer asks for English and German language skills.

Skills and tools named in the text include Python, SQL, Google Cloud and statistics.

No salary is given in this listing, so check the official pay figures in the DGJ Insight section below where they exist.

Benefits mentioned in the advert: paid time off and learning budget.

The advert does not mention visa sponsorship. If you would move to Switzerland for this job, check the official work permit route first (DGJ Insight lists it where we have it).

Dev Global Jobs found this job on Arbeitnow on Nov 5, 2026.

Employer
Grape Health
Location
Zürich, Switzerland
Work mode
hybrid
Job type
Full-time
Pay
Not stated by the employer
Languages asked
English and German
Found
Nov 5, 2026 on Arbeitnow
Employer text
1,337 words, about 6 min to read
Skills named in the advert
PythonSQLGoogle Cloudstatistics
Before you apply
  • Apply only on the official page (arbeitnow.ch). Dev Global Jobs is not the employer and never asks for a fee.
  • Mirror the skills the advert names (Python, SQL, Google Cloud and statistics) in your CV where you really have them; applicant tracking systems look for these words.
  • Say your level in English and German plainly (for example B2 or C1).
  • Read the employer’s full text below (about 6 min) before you apply.
  • Build or check your CV with the free DGJ CV Builder.
Only on Dev Global Jobs

DGJ Insight

Our own data about this role and place, from official statistics and our live job index.

Updated Nov 5, 2026
Pay benchmark
Average wage, Switzerland
CHF 98,334 average / year

Source: OECD Average annual wages, 2025

Cost of living · Geneva
102.7 vs New York = 100

UN living-cost index for Geneva (ICSC post adjustment 80.3), as of 1 Oct 2026.

Source: ICSC post adjustment classifications (icsc.un.org)

Work permit route
  • Work permit B / L (non-EU quota): Highly qualified specialists, employer proves no Swiss or EU candidate; annual quotas
  • EU/EFTA free movement permits: Registration for EU/EFTA nationals with a job

Official routes: State Secretariat for Migration (SEM)

Job description

About the role

Full text from the employer, as published on Arbeitnow, arranged into sections. Nothing added or removed.

🍇 About grape:    Our entrepreneurial spirit drives us in what we do and what we are passionate about. Our mission is to become the premier health partner in the insurance business. Recognising the need for innovation in the traditional employee insurance model we are set to revolutionize the employee insurance industry. We help companies support people before and after they get sick and to make more of their time. Our insurance solutions reduce monotonous and manual work for employees, doctors, HR & payroll managers. As we strive to lead a technology-driven transformation, we put employees first.   At grape we pride ourselves on our people and our culture. We continue to grow fast and that’s where you come in. Our team is dynamic, diverse and full of creative ideas. Want to join? We can’t wait to get to know you!

01Your role

Our data and tech give us an edge in risk assessment, pricing and premium calculation. This role turns that into accurate models that support our carrier partners and our growth, builds tuned models where they beat rules and off-the-shelf LLMs in claims (triage, intervention, return-to-work, fraud), and responsibly explores how data can help employees stay healthy through grape Care.

We’re looking for an applied ML engineer / data scientist to build predictive models from the ground up on real, regulated insurance data. You’ll own problems end to end, from effective-dated records to production, in a domain where correctness and responsible use genuinely matter.

Starting points include pricing and risk, portfolio monitoring, claims and payment patterns, triage and return-to-work, absence, and fraud detection. grape sits on a rich dataset, though, and you’ll help find the next high-value use cases. You’re candid about what the data can support, and you propose simpler approaches when they’re the right answer.

This is not an LLM role. LLM and agent workflows and document extraction sit with our engineering teams, and you’ll use their outputs as features.

What you'll do:

02Build and validate models

  • Own the full model lifecycle: feature engineering, training, evaluation, explainability, deployment, and drift monitoring.
  • Backtest on the historical book and run models in shadow mode alongside human decision-makers, reporting where and why they disagree.
  • Produce audit-ready validation and governance documentation that actuarial, compliance, and carrier partners can review.
  • 03Platform and MLOps

  • Deploy models on grape’s cloud platform within strict security and data-residency requirements for health data.
  • Set up experiment tracking, model versioning, and production monitoring, partnering with engineering on integration.
  • 04Shape the problem space

  • Identify and prioritize high-value use cases as you explore the dataset, rather than waiting to be handed problems.
  • Turn ambiguous business questions into well-defined, measurable modelling.
  • 05Responsible & explainable by design

  • Build privacy, fairness, and explainability into every model that touches personal or health data, working with compliance and legal on nDSG/GDPR boundaries.
  • Models support decisions; accountable owners make them. Pricing, reserving, and claims work requires licensed-actuary sign-off, and any automation requires governance approval first.
  • 06Collaborate

  • Explain model behavior and limits to underwriting, claims, actuarial, and compliance teams.
  • What you'll need:
  • Strong applied ML and statistics: supervised and unsupervised learning, anomaly detection, time-series, and survival/duration modeling.
  • Proven experience building models on real-world, relational, effective-dated data, including imbalanced outcomes.
  • Fluent Python (pandas, scikit-learn, a modern ML stack) and strong SQL.
  • Solid grasp of validation, calibration, and explainability (e.g. SHAP).
  • Production MLOps: experiment tracking, versioning, and drift monitoring.
  • Sound judgment on data privacy and modelling.
  • Fluent English.
  • Bias for action, ownership, and clear cross-functional communication.
  • Big plus:
  • Insurance, actuarial, or risk modeling (pricing, reserving, loss ratios).
  • Health, disability, or absence data, especially Swiss insurance (KTG, UVG); fraud detection in claims.
  • Regulated special-category data under nDSG/GDPR, or model risk management.
  • Google Cloud, including security-restricted deployments.
  • German language skills.
  • 🤝 What we offer in return: 🌱 Empowering workplace: Join a passionate team and an empowering workplace where you are given the ownership, tools, and support to make decisions and take initiative. Together we grow and build innovative solutions. 💻  Hybrid setup: Enjoy the flexibility of our hybrid work schedule, with the freedom to work remotely or from our office in Zurich. On Thursdays, our team day, we meet together in our Zurich office. 🪑 Home office stipend: To enable our hybrid setup, we allocate a one-off CHF 200.- home office budget to help you set up your dream workspace in the comfort of your own home. 🌐 Internet allowance: We give you a monthly internet allowance to help cover your internet costs at home and enable you to work seamlessly from your home office. ⏳ Flexible working time: You can distribute your working hours the way you want to. 🧠 Learning budget: We support you in improving your skills, acquiring new knowledge and advancing your career. We also allocate a CHF 1'500.- budget annually ❤️‍🩹  Well-being: Work-life balance is important to us and we foster a supportive work environment. We support you with mental health sessions with our partner Aepsy. 🎫  Team events: Every month we gather for fun and engaging events where we can connect and bond with our colleagues and our teams. ✈️  Team retreats: Once a year we travel somewhere nice to bond with our colleagues. 🚂  Travel and commute: We will cover your SBB half fare card, so we can spend some time together in the office. 🌴 Paid vacation: You get 5 weeks (25 days) of paid vacation every year and 2 additional days of paid vacation to compensate for canton-related holidays, religious holidays, birthdays, etc. The total amount of paid vacation days per year is 27 days. 🧖‍♀️ Wellness budget: Health and well-being looks different for everyone. You can optimize your wellness budget to best fit your needs. 👨‍👨‍👦‍👦 Parental and adoptive leave: We offer additional time off to support employees who are balancing family and work time in the most crucial stages of family life. ✈️ Digital nomad: For every 3 years of employment, you can work for an extended period of time from anywhere in the world (location subject to review).   🏁 Our recruitment process We place particular emphasis on four areas when making our selection decision: professional and technical skills, mindset & values. We evaluate these through the following steps:   Step 1 - Your motivation To get to know you better, we invite you to a 30-minute motivational interview with our Talent Acquisition Team. Step 2 - Role fit In the first interview, we assess how well your qualifications and skills align with the role requirements. This discussion will take place with your Hiring Manager. Step 3 - Case study For roles with higher technical demands, we will invite you to complete a case study or technical assessment. This allows us to better evaluate your specific skills and problem-solving abilities. Step 4 - Our culture connect Throughout the interview process, you'll gain insight into our company culture, and we'll explore how your values and mindset align with our ways of working. The final interview will offer a deeper look into this connection, along with broader discussions about the role and our vision.   Our diverse experiences, perspectives, and voices make us the company we are, and we would love to learn more about you! -------------------------------------------------------------------------- Health is our foundation. Innovation drives our mission. Together, we’re building the future of employee insurance. At grape, collaboration isn’t just a buzzword, it’s the foundation of how we work, live, and succeed. From bold brainstorms and lessons learned, we overcome challenges side by side. Our time together is our greatest asset. Disrupting an industry that truly needs change takes courage, creativity, and team spirit and that’s exactly what defines us. With well-being at the core, we foster an environment where ideas and people thrive. Your growth matters as much as our mission. Whether it’s supporting your self-care, developing new solutions, or redefining how health and insurance connect, we grow together. Our values guide us every step of the way: keeping Health at Heart, Inventing Together, and always striving to Embrace Clarity.

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