Data Governance Lead β€” Quality, Compliance & Insight in Nottingham

Data Governance Lead β€” Quality, Compliance & Insight in Nottingham

Nottingham Full-Time 60750 - 74250 Β£ / year (est.) Hybrid
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At a Glance

  • Tasks: Lead data governance and ensure compliance with GDPR and security protocols.
  • Company: Capital One, a leading financial services company with a focus on innovation.
  • Benefits: Hybrid work model, growth opportunities in AI, and competitive salary.
  • Other info: Join a forward-thinking team with excellent career advancement potential.
  • Why this job: Make a real impact on data quality and governance in a dynamic environment.
  • Qualifications: Experience in data stewardship and strong collaboration skills.

The predicted salary is between 60750 - 74250 Β£ per year.

Capital One is seeking a Lead Data Steward in Nottingham to drive data governance and stewardship across the UK business.

The role requires partnering with Data Owners and senior leaders to ensure data quality, descriptions, and lineage are maintained and compliant with GDPR and security protocols.

Based in Nottingham with a hybrid work model (office three days a week; home on Mon and Fri).

The role offers growth opportunities in AI-driven initiatives and enterprise data strategy.

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Data Governance Lead β€” Quality, Compliance & Insight in Nottingham employer: Capital One

Capital One is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. With a strong commitment to employee growth, we provide ample opportunities for professional development and leadership training, ensuring our team members thrive in their careers. The hybrid working model enhances work-life balance, making Capital One a rewarding place to contribute to meaningful projects in the global payments landscape.

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Contact Details:

Capital One Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Data Governance Lead β€” Quality, Compliance & Insight in Nottingham

✨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 Capital One!

✨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 Governance Lead β€” Quality, Compliance & Insight at Capital One.

✨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 Capital One.

✨Apply Directly through Our Website

When you find a suitable opening like Data Governance Lead β€” Quality, Compliance & Insight at Capital One, 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 Governance Lead β€” Quality, Compliance & Insight in Nottingham

Communication Skills
Stakeholder Management
Data Governance
Problem-Solving Skills
Python
Data Pipeline Development
Attention to Detail

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 Capital One, 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 Capital One. 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 Capital One

✨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 Capital One!

✨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.