Senior Bioinformatics Engineer

Job Description

We are looking for a highly motivated and adaptable person to join a growing team as a Bioinformatics Engineer. In this role, you will implement and run innovative data science solutions across a range of drug discovery activities to meet business needs. Specifically, you will incorporate large scale patient, genomic and functional datasets, use advanced statistical and artificial intelligence algorithms on them and guide drug discovery.

Responsibilities

1. Provide innovative solutions to complex biological problems to gain new insights into multiple aspects of drug discovery.
2. Develop and maintain production informatics pipelines.
3. Collaborate with colleagues across teams to translate business needs into high value IT solutions in a timely fashion.
4. Work to achieve scientific deliverables and milestones at agreed quality and timescales, identifying and mitigating risks as they emerge.
5. Establish appropriate communication with line manager, project team members and other stakeholders to ensure they are kept informed of workloads, issues, progress, results, innovation and developments.
6. Actively demonstrate best practice and behaviours to create a positive, productive and inclusive working environment.
7. Communicate analytical products and outputs to stakeholders.
8. Seek input and feedback from internal and external stakeholders about their requirements and prioritize your workload.
9. Interact with the executive team, project teams and external collaborators to aid in the delivery of projects.
10. Participate in the general duties of the company and pass on skills and knowledge to other team members.

Experience Required (E = Essential/D = Desirable)

1. A PhD in bioinformatics, biology or related scientific discipline or equivalent experience working in academia or industry (E)
2. At least 3 years’ experience of delivering computational solutions to complex biological problems (E)
3. Understanding of human genetics or drug discovery (E)
4. Advanced knowledge of programming in Python (E)
5. Experience in the analysis of large-scale genomic, functional genomic or clinical datasets using automated workflows, such as Nextflow (E)
6. Experience with cloud computing and software containerization (e.g. using Docker) (E)
7. Previous experience of developing, deploying and/or maintaining web user interfaces and/or dashboards (e.g. using Plotly Dash) (E)
8. Knowledge of current software development methodologies e.g. Scrum/Agile, CI/CD, Concurrent Version Systems (e.g. Git) (D)
9. Knowledge of cancer biology, cancer genetics, or cancer therapeutics (D)
10. Experience using statistical and/or artificial intelligence approaches, including but not limited to linear regression models, machine learning (elastic net, lasso, ridge regression) and neural networks (D)
11. Previous experience developing, deploying and maintaining IT platforms (D)
12. Knowledge of statistics and/or machine learning and experience with the relevant tools (e.g. BioConductor, Numpy, SciPy, Scikit-learn, Pandas or Keras) (D)
13. Experience with database management systems (D)