Senior Computer Scientist - BioAI

BioAI Senior Computer Scientist
Hybrid Working - 3 days on site, London
6 month rolling project, Inside IR35

emagine is a high-end professional services consultancy and solutions firm specialising in providing business and technology services to the financial services sector. We power progress, solve challenges, and deliver real results through tailored high-end consulting services and solutions.

We have created a culture of openness and integrity by building genuine and strong relationships and partnerships, enabling us to be uncompromising in our dedication to delivering the optimal service for our clients. Our commitment is not just towards our clients — we aim to foster a positive and equitable working environment with our consultants and colleagues, which stems from our core values: Confident, Dedicated, Responsible, Genuine.

As a Senior Principal Scientist (Computational Biology / AI), you will play a central role in advancing drug target discovery for cardiometabolic diseases (CMD) through rigorous computational modelling, large-scale data engineering, and applied machine learning. This role is rooted in hands-on computational science, where you will architect and implement scalable analytical pipelines, develop AI models, and translate complex biological datasets into predictive, decision-enabling outputs.

Operating within a globally distributed BioAI organisation, you will combine deep computational expertise with systems-level biological understanding to drive early-stage pipeline innovation.

Key Responsibilities

Computational Leadership & AI Development

• Lead the design and implementation of AI-driven analytical frameworks for drug target discovery.

• Develop, train, validate, and optimise machine learning and deep learning models on multimodal biological datasets.

• Apply advanced statistical learning, graph-based modelling, and network inference techniques to uncover causal biological mechanisms.

• Establish reproducible computational workflows and robust model evaluation pipelines.

Hands-on Computational Analysis

• Perform large-scale data processing and feature engineering on ultra-high throughput in-vitro screening datasets.

• Analyse high-dimensional data (cell painting, transcriptomics, proteomics, metabolomics) using systems biology and computational modelling approaches.

• Build scalable data pipelines for structured and unstructured biological datasets.

• Apply dimensionality reduction, clustering, representation learning, and integrative multi-omics modelling techniques.

• Conduct rigorous benchmarking, validation, and sensitivity analyses to ensure model robustness and biological interpretability.

Algorithm & Infrastructure Development

• Design scalable architectures for multimodal data integration across distributed compute environments.

• Optimise code for performance in high-performance computing (HPC) and cloud environments.

• Contribute to internal AI evaluation frameworks, including metrics for biological plausibility, predictive accuracy, and translational relevance.

• Implement version-controlled, containerised, and production-grade computational solutions.

Strategic & Cross-Functional Collaboration

• Translate complex computational findings into actionable biological hypotheses and drug target candidates.

• Partner with experimental scientists to iteratively refine computational models using wet-lab feedback.

• Influence systems biology strategy by defining computational standards, modelling approaches, and AI governance practices.

• Communicate complex technical insights clearly to scientific, technical, and executive stakeholders.

Required Qualifications & Experience

Educational Background

• Master’s degree or PhD in Computer Science, Computational Biology, Bioinformatics, Machine Learning, Systems Biology, or a related quantitative discipline.

Technical & Computational Expertise

• Strong hands-on experience in:

  • Python (NumPy, pandas, PyTorch, TensorFlow, scikit-learn) and/or R

  • Machine learning and deep learning for structured and high-dimensional data

  • Statistical modelling and causal inference

  • Network biology and graph-based learning approaches

• Experience building scalable data processing pipelines in cloud or HPC environments.

• Proven ability to independently design, implement, and validate computational models in production or research settings.

• Experience integrating multimodal datasets and handling noisy, incomplete biological data.

Industry Experience

• Significant experience in pharma, biotech, or tech-bio environments.

• Demonstrated impact in computational drug target identification or translational AI initiatives.

• Experience working in interdisciplinary teams bridging computational and experimental domains.

Preferred Qualifications

• PhD in Computer Science, Machine Learning, Computational Biology, or related quantitative field.

• Experience applying AI to cardiometabolic disease datasets.

• Background in cellular or molecular biology sufficient to contextualise computational outputs biologically.

• Experience developing interpretable AI frameworks for biomedical decision-making.

Our People

The ideal consultants will share our values and be aligned with our ways of working. As your career progresses, you can expect to work across all areas of the project lifecycle, from strategy to implementation. This will provide you with a broad base of experience from which to build an outstanding career.

The ideal consultants will share our values and be aligned with our ways of working and as your career progresses, you can expect to work across all areas of the project lifecycle.

We pride ourselves on;

• Providing our people with a supportive culture, rooted in our values and driven by our purpose.

• Promoting a culture of inclusion, collaboration, well-being, and learning and development.

• Providing increased agility and flexibility within our hybrid working model

• Investing in employees’ growth through ongoing training and development

• Autonomy to take ownership of projects, making decisions and demonstrating individual expertise

• Providing an transparent performance and career management experience.

Our consultants are integral to delivering successful consulting engagements, addressing our clients’ most pressing business challenges, and build lasting value in disciplines such as:

• Solve sophisticated, ambiguous business, change and technology problems, bringing structure and meticulous analysis and planning, acting, and taking decisions with little strategic direction

• Build, develop and sustain trusted senior client relationships in the C-suite by remaining highly attuned to client needs

• Drive, enable and support the business, partnering with our leaders, clients, and consultants across our practices to take the best of emagine to our clients through opportunity identification/qualification, solution development/presentation

Interested?

At emagine, we are committed to building an international and diverse team by embracing our different backgrounds.

If you are up to the challenge and would like to find out more, get in touch with us immediately, our internal recruitment team is always keen to hear from dynamic individuals that are looking to further their career and explore their full potential. 

“emagine is an equal opportunity employer, and employment practices are based strictly on merit. It is the policy of the Company to give equal opportunity in employment regardless of sex, sexual orientation, marital status, race, age, disability, gender reassignment, pregnancy and maternity, religion or ethnic origin”