Data Science Solutions Manager

Key Skills

Aartificial intelligence, Data Modeling, Data science techniques, Design, Effective communication skills, IT, Machine learning techniques, Post silicon validation, Statistics

Job Description

• Have a significant impact on the deployment of data science and process modeling capabilities across the technical development of UCB’s products (small molecules, biologics, and gene therapies)
• Partner with world-class scientific teams and together redefine the way we develop the manufacturing process of new drugs, leveraging data & predictive sciences to shorten cycles while ensuring an optimal yield and product quality
• Contribute to the establishment of a strong partner network, both internally within UCB and externally (industrial and academic partnerships), ensuring that we remain at the forefront of technological advancements in your area of expertise while making the most of existing assets.

For example, you will take the lead on the predictive modeling aspects of the NEMO (New Biological Entity End-to-End Modeling & Optimization) consortium project where UCB is collaborating with private & academic partners to leverage modeling & data science to optimize the development of new biologics.

You like to work in an environment where you will:

• Engage with key stakeholders from the various CMC Development Sciences teams to better understand their current challenges and opportunities, and together identify how data science approaches and in-silico modelling can transform the way we work for the better
• Translate these opportunities into clearly identified projects (scope, objectives, approach, budget, and planning) that are aligned with our long-term strategy, build on our key assets where possible, and fit within our roadmap
• Lead the delivery of these projects in collaboration with key stakeholders, including the scientists who will benefits from the delivered solutions and need to contribute to their design, development (e.g., through data) and testing, but also IT, validation, QA, external partners (where relevant), and other colleagues from the CMC Development Digital Sciences team
• Make sure that these data science and predictive modeling projects deliver their promises (or are stopped fast enough) and that the resulting solutions are properly integrated in our ways of working so that we realize their full benefits (change management)
• Influence our technology landscape where relevant (e.g., predictive modeling solutions) so that it supports our needs, while promoting rationalization/alignment where possible
• Work across boundaries, maintaining a proper level of alignment with partner departments like Early Solutions, Manufacturing and Regulatory Affairs
• Develop and maintain strong industrial and academic connections
• Stay abreast of new developments and trends in data science & predictive modeling, evaluating their relevance to the organization, and making recommendations for improvement

Interested? For this position you’ll need the following education, experience and skills:

• A Master’s degree (ideally PhD) in a quantitative discipline such as engineering, data science / artificial intelligence, computer science, mathematics, or statistics with a clear affinity for (bio-)pharmaceutical sciences or, alternatively, a degree in (bio-)pharmaceutical sciences with a strong background in advanced data analytics and modeling
• You have 5-8 years of relevant professional experience, amongst which:
• 3+ years in the (bio-)pharmaceutical industry or related (experience in the field of process development, discovery or manufacturing science & technology is a significant plus)
• 3+ years of experience in the field of data science and/or computational modeling / simulation
• Have the ability to understand the processes, activities, and challenges of scientific colleagues, translate them into a quantitative business problem to be solved, and report the results in a meaningful and clear manner for all audiences
• Have a practical experience with relevant data science and predictive modeling techniques (incl. machine learning, statistics, design of experiments, Bayesian optimization, knowledge graphs), and willingness to continue developing these stills to further improve and stay up-to-days with latest innovations
• Have an excellent communication, interpersonal and facilitation skills
• Demonstrate a strong business judgment, strategic thinking and be results oriented
• Demonstrate a real “Can do” attitude, ability to work independently and define and develop own targets
• Have the ability to drive change and navigate ambiguity when shaping new solutions in a corporate environment
• Have the ability to challenge established practices and processes when required