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Lead Data Scientist - Deep Learning Practitioner

Capital One

Lead Data Scientist - Deep Learning Practitioner

Capital One

2 Locations

·

On-site

·

Full-time

·

1w ago

Benefits & Perks

Pension scheme

Bonus

Healthcare

Parental Leave

Gym

Learning Budget

Healthcare

Parental Leave

Gym

Learning

Required Skills

Deep Learning

Python

Machine Learning

LSTMs

Transformers

Statistics

Leadership

White Collar Factory (95009), United Kingdom, London, London

  • Lead Data Scientist
  • Deep Learning Practitioner

About this role

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 Language 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 Language 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, language) using techniques such as LSTMs or transformers.

  • A proven track record leading model development, including setting the technical direction, project management, stakeholder comms, 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 Py Torch, Tensor Flow, 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 ethnic 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 Race At Work Charters, Stonewall and up Reach 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 – Race Equality and Culture Heritage group focuses on representation, retention and engagement for associates from minority ethnic groups and allies

  • Out Front – 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 female associates and allies focusing on developing future leaders, particularly for female talent in our industry

Capital One is committed to diversity 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.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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About Capital One

Capital One

A financial services company that provides banking, credit card, auto loan, savings, and commercial banking services.

10,001+

Employees

Mclean

Headquarters

$30B

Valuation

Reviews

3.2

6 reviews

Work Life Balance

2.2

Compensation

3.8

Culture

1.8

Career

2.5

Management

1.5

25%

Recommend to a Friend

Pros

Competitive compensation packages

High base salaries for roles

Performance bonuses available

Cons

Stack ranking system affecting job security

Poor interview process and communication

Mandatory office requirements

Salary Ranges

84 data points

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0 reports

$81,250

total / year

Base

$32,500

Stock

$40,625

Bonus

$8,125

$56,875

$105,625

Interview Experience

5 interviews

Difficulty

3.0

/ 5

Duration

14-28 weeks

Offer Rate

40%

Experience

Positive 40%

Neutral 60%

Negative 0%

Interview Process

1

Application Review

2

Online Assessment (CodeSignal)

3

Recruiter Phone Screen

4

Technical Interview

5

Behavioral Interview

6

Power Day/Super Day

7

Final Round/Offer

Common Questions

Coding/Algorithm

Data Analysis

Behavioral/STAR

Technical Knowledge

System Design