At a Glance
- Tasks: Develop deep learning models and collaborate on innovative projects to solve real business problems.
- Company: Join a forward-thinking company committed to diversity and innovation.
- Benefits: Competitive salary, generous leave, private medical insurance, and funding for qualifications.
- Other info: Hybrid work model with excellent career growth opportunities.
- Why this job: Make an impact with cutting-edge technology while growing your skills in a dynamic environment.
- Qualifications: Experience with deep learning models, Python, and strong communication skills.
The predicted salary is between 60000 - 80000 £ per year.
Location: London or Nottingham
Working Pattern: 3 days in-office (Tuesday-Thursday) and 2 days remote.
About the Role: Our Data Science team develops machine learning and deep learning solutions to solve business problems. This role focuses on building proprietary deep learning models for underwriting and supporting partners in developing advanced servicing products using large language models.
What you’ll do:
- Develop new deep-learning approaches to enhance underwriting models.
- Apply models to new (multi-modal) data types.
- Consult with tech and product partners to design, develop and launch LLM-powered products.
- Use coding, statistical skills and business acumen to extract actionable solutions from large datasets.
- Work cross-functionally on projects that support key business initiatives and drive sustainable growth.
Skills and experience you’ll need:
- Experience developing and deploying deep-learning models for sequential data (e.g., time series, language) using LSTMs or transformers.
- Hands-on experience with PyTorch, TensorFlow or Hugging Face Transformers.
- Familiarity with pre-training and fine-tuning large-scale models.
- Experience with structured and unstructured data, tokenisation techniques.
- Strong understanding of probability, statistics and machine learning, and ability to manipulate large data sets.
- Proficient in Python; able to adapt to new languages and technologies.
- Excellent communication skills for diverse business audiences.
- Drive for continued learning and development of industry-leading solutions.
Where and how you’ll work: This is a permanent position based in our Nottingham or London office. Work is hybrid: three days a week in the office (Tuesday-Thursday) and two days remote.
What’s in it for you:
- Competitive pension and performance-based bonus schemes.
- 25 days of annual leave, increasing with tenure (plus option to buy 5 additional days).
- Access to premium care through private medical insurance.
- Enhanced parental leave and family support.
- Up to £5,000 in funding for external qualifications.
Equal Opportunity Employment: Capital One is committed to diversity in the workplace.
Data Scientist / Deep Learning Practitioner employer: Capital One (Europe) plc
At Capital One, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London and Nottingham offices provide a hybrid working model, allowing for flexibility while ensuring team engagement. With competitive benefits, including generous annual leave, private medical insurance, and substantial funding for professional development, we are dedicated to supporting our employees' growth and well-being in a diverse and inclusive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist / Deep Learning Practitioner
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We think you need these skills to ace Data Scientist / Deep Learning Practitioner
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 (Europe) plc, 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 (Europe) plc. 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 (Europe) plc
✨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 (Europe) plc!
✨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.
