At a Glance
- Tasks: Develop machine learning models and generate insights from complex data to solve business challenges.
- Company: Join a dynamic team at a leading financial services company focused on innovation.
- Benefits: Enjoy competitive pay, flexible working, and access to extensive training and development.
- Other info: Diverse and inclusive workplace with strong support networks and career progression opportunities.
- Why this job: Make a real impact in the financial sector while working with cutting-edge technology.
- Qualifications: Experience in statistics, machine learning, and coding in Python is essential.
The predicted salary is between 50000 - 60000 £ per year.
Our Data Science team focuses on the development of machine learning and AI solutions, to solve business problems and deliver actionable insights. We are a talented, collaborative and enthusiastic group, who use our expertise to make sense of complex data, working in close collaboration with our business partners. This role will primarily focus on feature engineering and insight generation from new types of data and the development of machine learning models to address critical business challenges in underwriting.
We are interested in candidates who have experience working with Open Banking or Credit Bureau data. A deep grounding in statistics and experience of Model Risk Management is also welcomed.
What you'll do
- Develop and maintain the machine learning models which define our competitive advantage in the financial services market.
- Explore and evaluate data, using advanced feature generation and categorisation techniques, in order to stay at the forefront of innovation.
- Analyse tabular and non-tabular data, such as text, logs, or time series, to produce powerful new insights.
- Consult on complex statistical test design, to efficiently learn our way into new areas of the market.
- Use a combination of business acumen, coding and statistical skills to navigate large amounts of data and extract actionable solutions, working cross-functionally to support key business initiatives and drive sustainable growth.
What we're looking for
- A strong understanding of probability, statistics, machine learning, feature extraction and familiarity with large data set manipulation.
- Experience using deep learning models, particularly for sequential data.
- Familiarity with Open Banking or Credit Bureau data.
- Experience working with multi-modal data; in multiple formats from a variety of different sources.
- Experience in producing reliable and maintainable code in Python, with an ability to adapt to new languages and technologies.
- Experience of Model Risk Management; technical documentation, coding best practices, the importance of validation and ongoing monitoring.
- Natural curiosity and proactive engagement with all areas of the business, with a desire to ask questions, challenge the status-quo and identify where Data Science can add value.
- Ability to communicate findings to a diverse business focused audience, influencing others in both verbal and written form.
- A drive for continued learning through an internal and external focus, in order to develop enterprise and industry leading solutions.
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 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.
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 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 - Race Equality and Culture Heritage group focuses on representation, retention and engagement for associates from minority ethnic 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 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.
Data Scientist / Statistician Model Developer in Leicester employer: Capital One
Contact Detail:
Capital One Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist / Statistician Model Developer in Leicester
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or attend industry meetups. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Practice coding challenges and be ready to discuss your experience with machine learning and data analysis.
✨Tip Number 3
Show off your passion for data science! Bring examples of your work, whether it's projects, GitHub repos, or case studies. Let them see your enthusiasm and expertise in action.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining our team!
We think you need these skills to ace Data Scientist / Statistician Model Developer in Leicester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist / Statistician role. Highlight your experience with machine learning, feature engineering, and any relevant data sources like Open Banking or Credit Bureau data. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about data science and how you can contribute to our team. Be sure to mention specific projects or experiences that showcase your skills in statistics and model development.
Showcase Your Technical Skills: Don’t forget to highlight your coding abilities, especially in Python! If you've worked with deep learning models or have experience in Model Risk Management, make sure to include that. We love seeing candidates who can navigate large datasets and produce reliable code.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, we’re excited to see what you bring to the table!
How to prepare for a job interview at Capital One
✨Know Your Data Inside Out
Before the interview, dive deep into the types of data you'll be working with, especially Open Banking and Credit Bureau data. Familiarise yourself with how these datasets can be manipulated and analysed, as well as the latest trends in feature engineering. This will not only show your expertise but also your genuine interest in the role.
✨Showcase Your Statistical Skills
Be prepared to discuss your understanding of probability, statistics, and machine learning. Brush up on key concepts and be ready to explain how you've applied them in past projects. Consider bringing examples of statistical tests you've designed or models you've developed to illustrate your experience.
✨Communicate Clearly and Confidently
Since the role involves influencing a diverse audience, practice explaining complex data insights in simple terms. Use clear examples from your previous work to demonstrate how you’ve communicated findings effectively. This will highlight your ability to bridge the gap between technical and non-technical stakeholders.
✨Emphasise Continuous Learning
Express your passion for ongoing education in data science and related fields. Mention any recent courses, certifications, or projects that showcase your commitment to staying at the forefront of innovation. This aligns perfectly with the company’s focus on developing enterprise-leading solutions and shows you're proactive about your professional growth.