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- Tasks: Design and implement cutting-edge analytics and ML pipelines for genomics data.
- Company: Join a leading company in genomics with a focus on innovation.
- Benefits: Enjoy competitive salary, bonuses, healthcare, and hybrid working options.
- Other info: Collaborate with cross-functional teams and grow your career in a dynamic environment.
- Why this job: Make a real impact in genomics while working with advanced technologies.
- Qualifications: Strong Python programming skills and experience in data analysis required.
The predicted salary is between 60000 - 80000 £ per year.
Responsibilities
- Design and implement maintainable analytics and ML pipelines for genomics and multi‑omics data.
- Implement state‑of‑the‑art tools for dynamically analysing, interpreting, and visualising genetic and genomic data.
- Translate scientific and domain requirements into reliable, testable software systems.
- Own workflows from prototype through to usable, shareable capability.
- Apply machine‑learning methods to answer biological questions where appropriate, emphasising robustness, interpretability, and reproducibility.
- Contribute engineering best practices within a scientific environment (testing, code structure, documentation).
- Act as a technical bridge between genomics scientists and AI/ML or platform teams.
- Own pipelines end‑to‑end, building, running, and maintaining data or analytics pipelines using workflow orchestration frameworks such as Nextflow, Airflow, Dagster, Prefect or Snakemake.
- Work independently and take ownership of deliverables.
Required Qualifications
- Strong programming skills in Python.
- Demonstrated experience writing maintainable, production‑quality code with modular design, testing and version control.
- Knowledge of genetic, genomic, epigenomic or experimental/functional genomic data and relevant methods for data analysis and interpretation.
Preferred Qualifications & Skills
- Experience working in cross‑functional scientific or R&D teams.
- Practical experience implementing or operationalising machine‑learning models end‑to‑end (data preparation, training, evaluation, iteration).
- Experience deploying or operationalising ML models.
- Experience working in cloud‑based trusted research environments.
- Deep understanding of statistical genomics/genetics methodology.
Benefits and Working Conditions
- Competitive salary and annual bonus based on company performance.
- Healthcare and wellbeing programmes.
- Pension plan membership.
- Shares and savings programme.
- Hybrid working model through Performance with Choice programme.
GSK is an equal opportunity employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, colour, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.
Principal Scientist, Genomics Analytics Engineer in Stevenage employer: WISE Campaign
Contact Detail:
WISE Campaign Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Scientist, Genomics Analytics Engineer in Stevenage
✨Tip Number 1
Network like a pro! Reach out to folks in the genomics and AI/ML space on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving analytics and ML pipelines. This is your chance to demonstrate your coding prowess and problem-solving abilities.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to genomics and machine learning. We recommend practising with friends or using mock interview platforms to build confidence.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Principal Scientist, Genomics Analytics Engineer in Stevenage
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with genomics analytics and machine learning. We want to see how your skills align with the responsibilities listed in the job description.
Showcase Your Technical Skills: Don’t hold back on showcasing your programming prowess, especially in Python! Include examples of maintainable code you've written and any relevant projects that demonstrate your ability to build and maintain analytics pipelines.
Highlight Collaboration Experience: Since we value teamwork, share instances where you’ve worked in cross-functional teams. This could be anything from collaborating with scientists to bridging gaps between technical and non-technical teams.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity!
How to prepare for a job interview at WISE Campaign
✨Know Your Tech Stack
Make sure you’re well-versed in the tools mentioned in the job description, like Python and workflow orchestration frameworks. Brush up on your experience with Nextflow, Airflow, or similar tools, as you might be asked to discuss how you've used them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've applied machine learning methods to biological questions. Highlight your thought process and how you ensured robustness and interpretability in your solutions. This will demonstrate your ability to translate scientific requirements into actionable insights.
✨Emphasise Collaboration
Since the role involves acting as a bridge between genomics scientists and AI/ML teams, be ready to share experiences of working in cross-functional teams. Talk about how you’ve communicated complex technical concepts to non-technical stakeholders and vice versa.
✨Prepare for Technical Questions
Expect to dive deep into your coding practices and data analysis methodologies. Be prepared to discuss your approach to writing maintainable code, testing, and version control. You might even face a coding challenge, so practice writing clean, modular code ahead of time!