Senior Scientist - Data Science & AI, Industrial Process Analytics

Dsm Firmenich
Geneva, Switzerland
4 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Geneva, Switzerland

Tech stack

JavaScript
API
Artificial Intelligence
Amazon Web Services (AWS)
Data analysis
Azure
Cloud Computing
Code Review
Databases
Continuous Integration
Information Engineering
Django
Python
Machine Learning
Language Modeling
Software Construction
Software Engineering
Technical Data Management Systems
Data Processing
Data Ingestion
Flask
GIT
FastAPI
Pytest
Integration Tests
Information Technology
Code Inspection
Machine Learning Operations
Virtual Agents
Streamlit Framework
Docker
Databricks

Job description

  • Design, build, and ship scalable data science applications for manufacturing - from first idea to validated, deployed product.
  • Implement model- and data-driven approaches that support plant engineers and operators in day-to-day decisions.
  • Collaborate in multi-disciplinary teams (data scientists, process/chemical engineers, cloud & data engineers, reliability and production experts) to improve yield, throughput, quality, reliability, and sustainability.
  • Generate insights and convert them into measurable impact.
  • Champion a data-driven mindset across sites; communicate results with clarity to technical and non-technical stakeholders.
  • Contribute to best practices for data analysis, coding and MLOps.
  • Stay up to date with state-of-the-art methods, scout and implement new technology in-house

We offer:

  • Direct impact on manufacturing operations and sustainability KPIs.
  • A global Advanced Analytics team focused on optimizing biotech and chemical processes-fully aligned with dsm-firmenich's manufacturing excellence strategy.
  • Real-world challenges and exposure to all businesses. Opportunity to contribute strongly to both manufacturing operations as well as S&R up- and downscaling.
  • An experienced, supportive community that has optimized plants worldwide-and room to grow your expertise in both ML and manufacturing.

Requirements

  • PhD or similar experience in (Bio)Chemical Engineering or a related field, or Data Science/Statistics/Computer Science.
  • 3-7 years of additional academic or industrial work experience in manufacturing data science, ideally for (bio)chemical processes.
  • Strong hands-on Machine Learning expertise and rigorous, real-world validation
  • Modeling for industrial settings: you can dive into methods and details, yet make pragmatic calls in a results-driven environment.
  • Excellent communication and "domain translation" skills-partnering with engineers, operators, and leadership; navigating complex stakeholder landscapes.
  • Excellent problem-solving skills and proven ability to work both independently and collaboratively.
  • Ability to create end-to-end computational workflows, from data ingestion to deployment and monitoring.
  • Understanding of (bio)chemical processes and process control, ideally including:
  • Experience processing and modeling time-series, tabular, and panel/longitudinal/multi-way data; exposure to multivariate process analytics/chemometrics. Experience with MPC or system identification is a strong advantage.
  • Physics-based and hybrid modeling (e.g., gray-box, surrogate models, PINNs, digital twins) is a strong plus.
  • Familiarity with vision and text-based GenAI (for operator guidance, documentation mining, inspection, etc.) is a plus.

Technical skills

Advanced Analytics and Machine Learning

  • Python and core Data Science stack for data manipulation, visualization, statistics, ML/DL, and time-series/forecasting.
  • Multivariate modeling / Chemometrics for process monitoring and root-cause analysis.
  • Model interpretability and uncertainty

Software engineering & lifecycle

  • Software engineering best practices: git, code review, linting/formatting, unit/integration tests (pytest), packaging (uv), containers (Docker), exposure to CI/CD.
  • Familiarity with data engineering and model management (DBT, databases, MLFlow)

Nice to have

  • Process analytics with Seeq or TrendMiner
  • Causal & robust modeling: DoE/experiment design, Bayesian methods, causal inference, drift detection
  • Hybrid & control-aware modeling: physics-informed/gray-box models, surrogates for optimization, MPC integration.
  • GenAI, LLMOps, agentic AI, Vision Language Models
  • Cloud platforms, AWS, Azure, Databricks.
  • Online learning, IoT and edge scenarios, streaming and real-time
  • Workflows: Nextflow/CWL or alternatives for reproducible pipelines, Cora cloud pipeline
  • API and webapp development (FastAPI, Flask, Django, streamlit, JavaScript)

About the company

At dsm-firmenich, we don't just meet expectations - we go beyond them. Join our global team powered by science, creativity, and a shared purpose: to bring progress to life. From elevating health to making fortified food and sustainable skincare, the impact of your work here will be felt by millions - every single day. Whether it's fragrance that helps you focus, alternative meat that's better for the planet, or reducing sugar without losing flavor, this is where you help shape the future of nutrition, health, and beauty for everyone, everywhere. And while you're making a difference, we'll make sure you're growing too. With learning that never stops, a culture that lifts you up and the freedom to move across businesses, teams, and borders. Your voice matters here. And your ideas? They're essential to our future. Because real progress only happens when we go beyond, together. Inclusion, belonging and equal opportunity statement At dsm-firmenich, we believe being a force for good starts with the way we treat each other. When people feel supported, included, and free to be themselves, they do their best work - and that's exactly the kind of culture we're building. A place where opportunity is truly equal, authenticity is celebrated, and everyone has the chance to grow, contribute, and feel they belong. We're proud to be an equal opportunity employer, and we're serious about making our hiring process as fair and inclusive as possible. From inclusive language and diverse interview panels to thoughtful sourcing, we're committed to reflecting the world we serve.

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