At a Glance
- Tasks: Lead the development of deep learning models for underwriting and mentor fellow data scientists.
- Company: Join Capital One, a leader in financial technology, based in Nottingham.
- Benefits: Enjoy competitive pay, flexible working, and opportunities for professional growth.
- Other info: Work in a hybrid setup with a dynamic team focused on innovation.
- Why this job: Make a real impact by transforming data into actionable insights for customers.
- Qualifications: Experience in deep learning, Python, SQL, and mentoring skills required.
The predicted salary is between 63000 - 77000 £ per year.
Capital One is seeking a Lead Data Scientist / Deep Learning Practitioner in Nottingham to lead the development of proprietary deep learning models for underwriting.
You will work with diverse data to boost predictive power and generate actionable customer insights.
You’ll mentor others, collaborate with stakeholders, and drive prototypes through production, using Py Torch/Tensor Flow and SQL/Python in a hybrid Nottingham setup.
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Senior Deep Learning Lead for Underwriting AI in Nottingham employer: Capital One
At Capital One, we believe in empowering our employees to make a meaningful impact in their communities. As a Café Ambassador in the Bronx, you'll enjoy a vibrant work culture that prioritises inclusivity and personal growth, alongside a comprehensive benefits package that supports your well-being and career development. Join us to be part of a mission-driven team where your contributions are valued and you can thrive both personally and professionally.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Deep Learning Lead for Underwriting AI in Nottingham
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We think you need these skills to ace Senior Deep Learning Lead for Underwriting AI in Nottingham
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.
