Data Scientist

2 weeks ago

Oxford UK, Oxfordshire, United Kingdom Cranleigh STEM, Sustainability & SHEQ Recruitment Full time

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.

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