At a Glance
- Tasks: Analyse large data sets using machine learning and communicate findings effectively.
- Company: Join a leading research network focused on healthy ageing and metabolic science.
- Benefits: Competitive salary, generous leave, flexible working, and professional development opportunities.
- Other info: Full-time role with excellent career growth in a diverse and inclusive environment.
- Why this job: Make a real impact in the field of ageing while collaborating with top academics.
- Qualifications: Degree in data science or related field; experience with machine learning required.
The predicted salary is between 42405 - 45932 £ per year.
We are seeking a skilled data scientist and science communicator to support a new national research network around healthy ageing. The successful candidate will use machine learning techniques to analyse large data sets held within the network, with the aim of producing novel findings within the field of metabolic ageing. The role will involve engaging with academics across Queen Mary and externally, including writing reports, newsletters, and presenting at events.
You will have a degree or relevant professional experience in data science or another related quantitative/scientific discipline. You will have experience using machine learning techniques and will be confident in communicating your findings to a range of specialist and non-specialist audiences.
The network is funded by the BBSRC-MRC’s Ageing across the life course interdisciplinary research network call. This national network of stakeholders is led by Profs Chan and Henson and aims to tackle CELLular metabolism Over a life-course in socioeconomically disadvantaged populations (CELLO).
We offer competitive salaries, access to a generous pension scheme, 30 days’ leave per annum (pro‑rata for part‑time/fixed‑term), a season ticket loan scheme and access to a comprehensive range of personal and professional development opportunities. In addition, we offer a range of work‑life balance and family‑friendly, inclusive employment policies, flexible working arrangements, and campus facilities including an on‑site nursery at the Mile End campus.
The post is based at the Charterhouse Square Campus in London. It is full time (35 hours per week), fixed‑term appointment for 10 months, with an expected start date of May 2024. The starting salary will be Grade 5, £42,405 – £45,932 per annum, inclusive of London Allowance.
Queen Mary’s commitment to our diverse and inclusive community is embedded in our appointments processes. Reasonable adjustments will be made at each stage of the recruitment process for any candidate with a disability. We are open to considering applications from candidates wishing to work flexibly.
Data Scientist and Science Communicator employer: Queen Mary University of London
Queen Mary University offers an exceptional work environment for data scientists and science communicators, fostering a culture of collaboration and innovation in the field of healthy ageing. With competitive salaries, generous leave, and a commitment to work-life balance, employees benefit from professional development opportunities and inclusive policies that support diverse needs. Located in the vibrant Charterhouse Square Campus in London, this role provides a unique chance to engage with leading academics and contribute to impactful research.
Contact Details:
Queen Mary University of London Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist and Science Communicator
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of data science and healthy ageing. Attend events, webinars, or even local meetups to connect with potential colleagues and mentors. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects and data analyses. This is your chance to demonstrate your expertise and make a lasting impression. Don’t forget to include any reports or presentations you've done – they highlight your communication skills too!
✨Tip Number 3
Practice makes perfect! Prepare for interviews by rehearsing common questions related to data science and science communication. Think about how you can explain complex concepts in simple terms, as you'll need to engage with both specialists and non-specialists.
✨Tip Number 4
Apply through our website! We love seeing applications directly from candidates who are genuinely interested in joining our team. Tailor your application to highlight your relevant experience and passion for healthy ageing – it’ll make you stand out!
We think you need these skills to ace Data Scientist and Science Communicator
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in data science and machine learning. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about healthy ageing and how your communication skills can help us engage with diverse audiences. Keep it engaging and personal!
Showcase Your Communication Skills:Since this role involves presenting findings and writing reports, include examples of how you've effectively communicated complex data to both specialists and non-specialists. We love seeing clear, concise communication!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your materials and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Queen Mary University of London
✨Know Your Data Inside Out
Before the interview, dive deep into the data sets you might be working with. Familiarise yourself with the types of data and machine learning techniques relevant to metabolic ageing. This will not only help you answer technical questions confidently but also show your genuine interest in the role.
✨Communicate Clearly and Effectively
Since the role involves engaging with both specialists and non-specialists, practice explaining complex concepts in simple terms. Prepare examples of how you've communicated findings in the past, whether through reports or presentations, to demonstrate your ability to bridge the gap between data and audience.
✨Showcase Your Collaborative Spirit
Highlight any experience you have working in interdisciplinary teams. The role requires collaboration with academics and stakeholders, so be ready to discuss how you've successfully worked with others to achieve common goals, especially in research settings.
✨Prepare Questions About the Project
Come prepared with insightful questions about the CELLO project and its objectives. This shows that you're not just interested in the job, but also in contributing to the network's mission. It’s a great way to demonstrate your enthusiasm and understanding of the field.
