Our start-up client is expanding their Data Science team and are excited to welcome a Data Scientist who will collaborate closely with their R&D team.
In this role, you'll leverage advanced computational and machine learning/deep learning approaches to support their cell line development programs.
Your work will drive innovation in mammalian cell line engineering, media formulation, and bioprocess development.
You'll be embedded in a diverse team of biologists, automation scientists, and chemical engineers.
Meeting project deadlines and delivering impactful results will be second nature, especially if you have a track record of contributing to commercial products.
Most importantly, you're looking for a meaningful role where your expertise can make a difference.
Key Responsibilities: Develop models, algorithms, and performance evaluations from both internal and external datasets, using cutting-edge machine learning techniques to analyze cell culture experimental results.
Apply and refine AI/ML methods (e.g., classification, clustering, deep learning) to research datasets—such as cell culture, Design of Experiments (DoE), media formulation, and bioprocess optimization—to automate data review, improve decision-making, and deepen bioprocess understanding.
Collaborate daily with research scientists and bioprocess engineers in R&D, focusing on cell culture, media development, and bioprocess optimization.
Contribute to experimental design, customized data visualization, and analysis solutions aligned with study objectives.
Innovate new quantitative methods and uncover novel analysis opportunities by integrating diverse data sources.
Share findings with interdisciplinary project teams and stakeholders, serving as a knowledge resource on statistical and AI/ML methodologies.
Stay current on recent advancements in data science and AI/ML/DL to ensure we remain at the forefront of our field.
What We're Looking For: They need someone skilled in analysing multi-dimensional datasets—from in vitro cell culture studies to large-scale bioprocess optimization—contributing to an advanced end-to-end in silico modelling platform.
Skills and Qualifications: Educational Background : M.Sc.
or Ph.D. in AI/ML, Data Analytics, or a related field (e.g., Computer Science, Mathematics, Statistics, Physics, Biophysics, Computational Biology, or Engineering Science).
Experience : Industry experience in biopharma/biotech preferred, with demonstrated success in applying ML/Deep Learning.
Technical Expertise : Proficient in advanced statistics, ML/DL methods, and various network architectures (e.g., CNNs, GANs, RNNs, Auto-Encoders, Transformers, PLMs).
Skilled in data manipulation and programming.
Proficiency in data analysis tools (e.g., Python, R) and deep learning libraries (e.g., PyTorch, TensorFlow, Keras).
Familiar with data visualization and dimensionality reduction techniques.
Capable of developing, benchmarking, and deploying predictive algorithms.
Experience working in cloud or high-performance computing environments (e.g., GCP, AWS).
Preferred Knowledge : Familiarity with mammalian cell line and bioprocess development is a plus.
Team Collaboration : Comfortable working in a cross-functional team, building close working relationships with scientists across R&D.
Qualities for Success : Problem-solving mindset and lateral thinking Strong organizational and time management skills Ability to balance multiple projects Clear, confident communicator (both written and verbal) Team-oriented but equally effective working independently to meet deadlines Salary: £DOE, Bonus, Excellent Benefits Package, inc.
Private Health Insurance and Company Shares, team get togethers, company parties, a well-stocked kitchen and free flowing tea, coffee, soft drinks and snacks.
They foster a strong team culture with plentiful collaboration, so onsite work is encouraged.
This role offers a hybrid option, with 3 days a week onsite.