Solution Data Scientist (m/w/d)

Proclinical Staffing; Deutschland; Vor Ort; EUR 55.000 - 85.000; Vollzeit

Zusammenfassung

A leading recruitment firm in the biopharma sector is seeking a Solution Data Scientist to manage end-to-end customer projects. The ideal candidate will have a MSc or PhD, strong data science skills, and experience in customer-facing roles. This position involves applying statistical and machine learning techniques to bioprocess data and effectively communicating findings to clients. If interested, please reach out to Thomas Wenig at [e-mail].

Qualifikationen

• Prior experience in a customer-facing data science or scientific consulting role is required.
• Strong background in data science, applied mathematics, or computational biology.
• Outstanding communication skills to convey complex modeling concepts.

Aufgaben

• Lead and manage customer modeling projects from data acquisition to result delivery.
• Apply statistical modeling, machine learning, and hybrid modeling techniques.
• Communicate results and insights effectively to scientific and non-technical audiences.

Kenntnisse

Statistical modeling

Machine learning

Hybrid modeling techniques

Python

Data visualization

Communication

Ausbildung

MSc or PhD in Data Science, Systems Biology, Bioprocess Engineering, or related field

Tools

NumPy

Pandas

SciPy

PyTorch

JAX

Scikit-learn

Jobbeschreibung

Are you a data scientist with a passion for analytical depth, scientific curiosity, and clear communication? Looking to guide customers in leveraging advanced AI-driven digital twins for bioprocess optimization?

Proclinical is seeking a highly motivated and scientifically minded Solution Data Scientist to join our customer-facing data science team. In this role, you will manage customer projects end-to-end: From data intake and preprocessing to building hybrid models using our proprietary technology and delivering scientifically sound and actionable insights to our clients.

You will act as the technical bridge between our customers and our modeling platform-capable of understanding biological processes, interpreting model results, and communicating them in a clear, impactful, and business-relevant way.

Responsibilities

Customer Project Execution

• Lead and manage customer modeling projects from data acquisition to result delivery.
• Build, calibrate, and validate hybrid models combining mechanistic and AI-based approaches.
• Translate biological and process data into predictive models of cell culture behavior.

Data Science and Modeling

• Apply statistical modeling, machine learning, and hybrid modeling techniques to bioprocess data.
• Design and execute virtual experiments to predict and optimize process performance.
• Ensure scientific rigor, reproducibility, and documentation quality throughout the modeling process.

Customer Engagement and Communication

• Communicate results and insights effectively to both scientific and non-technical audiences.
• Collaborate with customers to define modeling goals, interpret outcomes, and identify opportunities for further value creation.
• Serve as a trusted advisor and key technical contact during and after project execution.

Cross-Functional Collaboration

• Work closely with application scientists, ML engineers, and product teams to enhance our modeling workflows.
• Contribute to the continuous improvement of internal tools, best practices, and modeling frameworks.

Key Skills and Requirements

• MSc or PhD in Data Science, Systems Biology, Bioprocess Engineering, Computational Biology, or related field.
• Prior experience in a customer-facing data science or scientific consulting role.
• Experience with hybrid or mechanistic modeling of biological systems.
• Familiarity with biopharmaceutical development or process modeling workflows.
• Strong background in data science, applied mathematics, or computational biology.
• Proficiency in Python and relevant data science/ML libraries (NumPy, Pandas, SciPy, PyTorch, JAX, Scikit-learn).
• Understanding of mechanistic modeling concepts (ODEs, kinetic models, or hybrid modeling approaches).
• Familiarity with bioprocess or omics data is highly desirable.
• Profound experience in data visualization, model validation, and result presentation.
• Working knowledge of cloud environments (Azure, AWS, or GCP) is a plus.
• Outstanding communication skills, capable of conveying complex modeling concepts to executive stakeholders and cross-functional teams.
• Strategic thinking with a proven ability to align technical initiatives with business objectives.
• Leadership and mentoring abilities to inspire and grow technical teams.
• High-level problem-solving mindset and passion for innovation in biopharma digitalization.

If you are having difficulty in applying or if you have any questions, please contact Thomas Wenig at [e-mail].

If you are interested in applying to this exciting opportunity, then please click 'Apply' or to speak to one of our specialists please request a call back at the top of this page.

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