Data Scientist (Statistics and Machine Learning)

Job title: Data Scientist (Statistics and Machine Learning)

Company: Cranleigh Recruitment


Job description: 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.

Expected salary:

Location: Oxfordshire

Job date: Sat, 02 Nov 2024 02:42:41 GMT

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