At a Glance
- Tasks: Design and implement mathematical models to tackle national challenges in health and climate.
- Company: Join a leading department in Data Science and AI with a focus on collaboration.
- Benefits: Flexible working options, hybrid model, and commitment to diversity and equality.
- Other info: Dynamic, cross-disciplinary environment with opportunities for professional growth.
- Why this job: Make a real impact on pressing global issues while advancing your skills in data science.
- Qualifications: PhD or relevant experience in Mathematics, Statistics, or related fields; programming skills in Python/MATLAB.
The predicted salary is between 50000 - 70000 £ per year.
The Department of Data Science and AI is seeking a researcher to contribute to projects across national challenges such as life science, health, climate, and environmental sciences. The role involves developing new collaborations with NPL, government, industry, and academia, and applying advanced mathematical modelling to statistical inference, machine learning, and AI estimation methods.
Responsibilities
- Design and implement mathematical models.
- Develop and evaluate inference, ML, and AI techniques.
- Write reports and conduct literature reviews.
- Collaborate cross‑disciplinarily with team members and external partners.
- Contribute to the scientific community through sharing knowledge and insights.
Essential Experience
- Advanced knowledge in at least one area of mathematical modelling (e.g., stochastic processes, differential geometry, topology) and associated estimation methods.
- Eagerness to learn about different types of models.
- Experience in mathematical modelling and/or data analysis.
- Interest in theoretical guarantees for estimation methods and their applications.
- A PhD in a relevant subject or significant relevant working experience, such as Mathematics, Statistics, or a related degree with a strong statistical analysis background.
- Programming experience in Python and/or MATLAB, with an eagerness to work with an imperative programming language.
- Confidence in report writing and literature review.
- Experience working in a cross‑disciplinary environment.
- Strong problem‑solving skills.
Desirable Experience
- Experience in environmental and climate science, or health.
- Understanding or willingness to learn uncertainty quantification in complex systems.
- Experience with object‑oriented programming and continuous integration / continuous development software development frameworks including unit testing.
- Experience with assurance testing.
Location and Working Arrangements
The role is based in Teddington, with the possibility of working from the Cambridge location. We operate in a hybrid model that combines remote and office work, offering full‑time, part‑time, or flexible options where business needs permit.
Equal Opportunity Employer
NPL and DSIT have strong commitments to diversity and equality of opportunity and welcome applications from candidates irrespective of their background, gender, race, sexual orientation, religion, or age, provided they meet the required criteria. Applications from women, disabled and black, Asian and minority ethnic candidates in particular are encouraged. All disabled candidates as defined by the Equality Act 2010 who satisfy the minimum criteria for the role will be guaranteed an interview under the Disability Confident Scheme.
Data Scientist in Teddington employer: National Physical Laboratory (NPL)
At NPL, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation in the fields of data science and AI. Our commitment to employee growth is evident through our support for continuous learning and development, alongside flexible working arrangements that cater to diverse needs. Located in Teddington, with opportunities to engage in impactful projects across health, climate, and environmental sciences, we provide a unique environment where your contributions can make a real difference.
Contact Details:
National Physical Laboratory (NPL) Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Teddington
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like National Physical Laboratory (NPL)!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Scientist at National Physical Laboratory (NPL).
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like National Physical Laboratory (NPL).
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist at National Physical Laboratory (NPL), make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Scientist in Teddington
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!
Craft a Tailored Cover Letter:For a full-time role at National Physical Laboratory (NPL), your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at National Physical Laboratory (NPL). 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 National Physical Laboratory (NPL)
✨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!
✨Showcase Your Projects
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
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at National Physical Laboratory (NPL)!
✨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.
