At a Glance
- Tasks: Lead the development of innovative deep learning models to tackle real business challenges.
- Company: Join a forward-thinking tech company committed to diversity and inclusion.
- Benefits: Enjoy competitive pay, flexible working, and access to extensive training programmes.
- Other info: Collaborative environment with excellent career growth opportunities and modern office facilities.
- Why this job: Make a significant impact in the world of data science and machine learning.
- Qualifications: Strong experience in deep learning and coding, with a passion for innovation.
The predicted salary is between 70000 - 90000 £ per year.
Our Data Science team focuses on the development of Machine Learning and Deep Learning solutions, to solve business problems and deliver actionable insights. We are a talented, collaborative and enthusiastic group, who use our expertise to derive insights from complex data, working in close collaboration with our business partners.
This role will primarily focus on leading the development of proprietary deep learning models to address critical business challenges in underwriting. The role will also involve supporting our business partners as they develop advanced servicing products using Large Models.
What you’ll do:
- Lead the development of new deep learning approaches to advance our current underwriting models, which form the heart of our lending business. Apply these to new types of (multi-modal) data in order to stay at the forefront of innovation.
- Prioritise and own the roadmap for this work. Balancing R&D with in-market results, you will drive ideas from prototypes through to production.
- Provide consultancy to our tech and product partners, to help design, develop and launch products powered by Large Models (LLMs). This collaboration will help provide seamless experiences for our customers and associates.
- Use a combination of business acumen, coding and statistical skills to navigate large amounts of data and extract actionable solutions.
- Work cross-functionally on projects that support key business initiatives and drive sustainable growth.
What we’re looking for:
- Strong experience developing and deploying deep learning models, particularly for sequential data (e.g. time series), using techniques such as LSTMs or transformers.
- A proven track record leading model development, including setting the technical direction, project management, stakeholder communications, and mentoring junior members of the team.
- Experience producing and managing reliable and maintainable code in Python in a team setting, including code reviews and setting software engineering best practices.
- Hands-on experience with modern Machine/Deep Learning frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.
- Familiarity with both pre-training and fine-tuning of large-scale models.
- Experience working with structured and unstructured data, such as text, logs, or time series and tokenisation techniques.
- A strong understanding of probability, statistics, machine learning and familiarity with large data set manipulation.
- A drive for continued learning through an internal and external focus, and an ability to prototype new techniques to assess value.
We are committed to creating a level playing field and seek to create teams that are representative of our customers and the communities we serve. We’d love to hear from you if you identify with a typically under-represented group in our industry and are particularly keen to hear from women, the LGBTQ+ community and minority candidates.
Where and how you'll work:
This is a permanent position based in our Nottingham or London office. We have a hybrid working model, so you’ll be based in our office 3 days a week on Tuesdays, Wednesdays and Thursdays, and can work from home on Monday and Friday. Many of our associates have flexible working arrangements, and we're open to talking about an arrangement that works for you.
What’s in it for you:
- Bring us all this - and you’ll be well rewarded with a role contributing to the roadmap of an organisation committed to transformation.
- We offer high performers strong and diverse career progression, investing heavily in developing great people through our Capital One University training programmes (and appropriate external providers).
- Immediate access to our core benefits including pension scheme, bonus, generous holiday entitlement and private medical insurance – with flexible benefits available including season-ticket loans, cycle to work scheme and enhanced parental leave.
- Open-plan workspaces and accessible facilities designed to inspire and support you. Our Nottingham head-office has a fully-serviced gym, subsidised restaurant, mindfulness and music rooms. In London, you can heighten your mood with a run on our rooftop running track or an espresso at the Workshop Coffee café.
What you should know about how we recruit:
We pride ourselves on hiring the best people, not the same people. Building diverse and inclusive teams is the right thing to do and the smart thing to do. We want to work with top talent: whoever you are, whatever you look like, wherever you come from. We know it’s about what you do, not just what you say. That’s why we make our recruitment process fair and accessible. And we offer benefits that attract people at all ages and stages.
We also partner with organisations including the Women in Finance and At Work Charters, Stonewall and upReach to find people from every walk of life and help them thrive with us. We have a whole host of internal networks and support groups you could be involved in, to name a few:
- REACH – Equality and Culture Heritage group focuses on representation, retention and engagement for associates from minority groups and allies.
- OutFront – to provide LGBTQ+ support for all associates.
- Mind Your Mind – signposting support and promoting positive mental wellbeing for all.
- Women in Tech – promoting an inclusive environment in tech.
- EmpowHER - network of associates and allies focusing on developing future leaders, particularly for talent in our industry.
Capital One is committed to inclusivity in the workplace. If you require a reasonable adjustment, please contact ukrecruitment@capitalone.com. All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment.
Lead Data Scientist - Deep Learning Practitioner in Nottingham employer: Energy Jobline ZR
Capital One is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of Nottingham. With a strong commitment to employee growth through extensive training programmes and a focus on diversity and inclusion, associates enjoy flexible working arrangements and access to modern facilities, including a fully-serviced gym and mindfulness rooms. Join us to be part of a transformative journey in banking, where your contributions directly impact our mission to help customers succeed.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist - Deep Learning Practitioner in Nottingham
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your deep learning expertise. Be ready to discuss your past projects and how they relate to the role. We want to see your passion and problem-solving skills in action!
✨Tip Number 3
Don’t just apply; engage! When you find a role that excites you, reach out to the hiring manager or team members. Show genuine interest in their work and ask insightful questions. This can set you apart from other candidates.
✨Tip Number 4
Utilise our website to apply directly! It’s the best way to ensure your application gets noticed. Plus, it shows you’re keen on joining our team at StudySmarter, where we value innovation and collaboration.
We think you need these skills to ace Lead Data Scientist - Deep Learning Practitioner in Nottingham
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Lead Data Scientist role. Highlight your experience with deep learning models and how it aligns with our goals at StudySmarter. We want to see how you can bring your unique skills to our team!
Showcase Your Projects:Don’t just list your skills; show us what you’ve done! Include specific projects where you've developed or deployed deep learning models. This gives us a clear picture of your hands-on experience and how you tackle real-world problems.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language and avoid jargon unless necessary. We appreciate a well-structured application that gets straight to the point, making it easy for us to see your qualifications.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets to the right people. Plus, you’ll find all the details about the role and our company culture there!
How to prepare for a job interview at Energy Jobline ZR
✨Know Your Deep Learning Stuff
Make sure you brush up on your deep learning knowledge, especially around LSTMs and transformers. Be ready to discuss how you've applied these techniques in real-world scenarios, as this will show your practical experience and understanding.
✨Showcase Your Project Management Skills
Since the role involves leading model development, be prepared to talk about your experience in project management. Highlight specific projects where you set the technical direction and managed stakeholder communications effectively.
✨Demonstrate Your Coding Proficiency
You’ll need to prove your coding skills in Python, so be ready to discuss your experience with code reviews and best practices. Bring examples of reliable and maintainable code you've produced, and be prepared to explain your thought process.
✨Be Ready for Cross-Functional Collaboration
This role requires working closely with tech and product partners, so think of examples where you've successfully collaborated across teams. Emphasise your ability to communicate complex data insights in a way that’s accessible to non-technical stakeholders.