Data Science & AI Developer β€” Hybrid, Public Sector in England

Data Science & AI Developer β€” Hybrid, Public Sector in England

England Full-Time 37800 - 46200 Β£ / year (est.) Hybrid
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At a Glance

  • Tasks: Identify and apply data and AI solutions to drive innovation in the public sector.
  • Company: Join a forward-thinking organisation committed to ethical data practices.
  • Benefits: Enjoy hybrid working, competitive salary, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on governance and ethics.
  • Why this job: Make a real difference by leveraging data and AI for impactful solutions.
  • Qualifications: Experience in data science and AI development is essential.

The predicted salary is between 37800 - 46200 Β£ per year.

ONR is seeking a Data Scientist and AI Developer to grow data science and AI capability across the organisation.

You will identify opportunities to apply data and AI to deliver innovative solutions while ensuring governance, ethics and data protection are integral to decision making.

You will develop, test, deploy and maintain AI outputs, bringing data from multiple sources to generate insights and supporting business needs.

Hybrid working with regular office presence at Bootle is expected.

Data Science & AI Developer β€” Hybrid, Public Sector in England employer: ONR

ONR provides a unique opportunity to work at the forefront of nuclear regulation, contributing to national safety and environmental goals. The organization fosters a culture of continuous improvement and professional growth, making it an attractive employer for those passionate about public safety and technological advancement.

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Contact Details:

ONR Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Data Science & AI Developer β€” Hybrid, Public Sector in England

✨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 ONR!

✨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 Science & AI Developer β€” Hybrid, Public Sector at ONR.

✨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 ONR.

✨Apply Directly through Our Website

When you find a suitable opening like Data Science & AI Developer β€” Hybrid, Public Sector at ONR, 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 Science & AI Developer β€” Hybrid, Public Sector in England

Data Science
AI Development
Data Analysis
Governance
Ethics
Data Protection
Insight Generation

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 ONR, 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 ONR. 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 ONR

✨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 ONR!

✨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.