At a Glance
- Tasks: Implement AI infrastructure to unlock scientific data and accelerate treatment discovery.
- Company: Join Roche, a leader in life sciences with a focus on innovation.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Onsite work three days a week in a dynamic and collaborative environment.
- Why this job: Make a real impact by collaborating with scientists and ML experts in groundbreaking projects.
- Qualifications: Experience in machine learning and a passion for computational engineering.
The predicted salary is between 55000 - 65000 £ per year.
Roche is seeking a Machine Learning Engineer to implement infrastructure that unlocks scientific data and accelerates discovery of treatments. You will work at the intersection of computational engineering and biology, partnering with scientists, ML experts, and DevOps engineers to put AI tools into the hands of researchers.
This role is based in Welwyn, with onsite work three days per week. You will own features end-to-end from evaluation to production, shaping architecture and development.
ML Engineer, Life Sciences Data & Deployment (Onsite Welwyn) employer: NLP PEOPLE
At JPMorganChase, we pride ourselves on being an exceptional employer, offering a vibrant work culture that fosters innovation and collaboration. As an Applied AI ML Lead in Payments, you will not only have the chance to make a significant impact on global finance but also benefit from extensive career growth opportunities and mentorship within a diverse team. Our commitment to excellence and continuous learning ensures that your unique perspective is valued, making this an ideal environment for those looking to push the boundaries of technology in a meaningful way.
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer, Life Sciences Data & Deployment (Onsite Welwyn)
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We think you need these skills to ace ML Engineer, Life Sciences Data & Deployment (Onsite Welwyn)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at NLP PEOPLE. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at NLP PEOPLE
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
