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Data Science Degree Apprenticeship
3 months ago
Data Science Degree Apprenticeship
London (Hybrid)
Let's make the most of your talent
Minimum Salary £25,000 DOE
We believe in the power of fresh perspectives and untapped potential. Whether you're starting your career, looking for a career change, or returning to work, our apprenticeships offer the opportunity to grow, learn and earn simultaneously. You'll gain qualifications, develop new skills and lay the groundwork for an exciting future.
We're searching for budding Data Science Apprentices to join our team on a hybrid basis (following an initial training period) at our London office. During this 3 year programme you will rotate through the different functions within both our Actuarial and Pricing & Underwriting teams to learn about insurance, statistics, actuarial techniques, machine learning, economics, data analysis and visualisation, whilst working towards a BSc (Hons) in Data Science with BPP University.
About Us:
At Direct Line Group (DLG), insurance is just the start. Combining decades of industry experience with talented people in every field, we're a customer-obsessed market powerhouse. And we all work together to be brilliant for customers, every single day.
Speed, simplicity, and a common-sense human touch. It's what we do. And we do it well. We connect our customers with the very best in motor, home, commercial, and other personal lines insurance - anytime, from anywhere. We've been changing the game for insurance since 1985. And with several of the UK's most trusted brands under our wing, we've developed a reputation as one of the UK's most trusted insurance businesses.
What you'll do:
You'll learn to use statistical, actuarial and machine learning techniques to analyse and model insurance data. Working closely with actuaries, pricers, underwriters and data scientists to understand the drivers of insurance claims, you will reserve insurance liabilities, calculate economic capital requirements and develop pricing models that accurately reflect risk and customer behaviours. Additionally, we'll support you to seek out new opportunities to apply data science techniques to insurance and support those around you to grow and develop, sharing your expertise and best practice with your teams.
Key Job Responsibilities:
- Support the delivery of your department's pricing & underwriting or actuarial objectives.
- Improve DLG pricing performance and longer-term capability while maintaining pricing & underwriting discipline.
- Support reserving deep dives and the parametrisation of the internal economic capital model, including sensitivity analyses, validation exercises and financial reporting.
- Research build models for specific tasks for pricing, reserving and capital modelling, or for other uses, ensuring that these use appropriate techniques and data and are effective, efficient, high quality, documented and verifiable.
- Use your technical and analytical skills to develop innovative solutions to challenging problems.
- Deliver all activity in line with DLG governance and control frameworks acting as a champion for strong compliance.
- Liaise with peers across teams to investigate specific issues or formulate key assumptions to support the robustness of analysis undertaken.
- Communicate effectively, to colleagues and team managers, the impact and conclusion of work undertaken, particularly in identifying model or data issues and suggest appropriate remedial actions; produce draft of reports on specific areas.
- Contribute to cross departmental meetings and present back learning & issues to the Actuarial/Pricing team; support line manager in stakeholder meetings; build relationships with colleagues in other departments.
- Develop yourself in order to maximise your personal contribution to the job; actively share knowledge and experience within your scope of work, with other department members
What we are looking for:
You'll need to enjoy working with data, have an analytical mindset and a passion for learning, alongside meeting the minimum eligibility requirements for the role, which are:
Applicants need to have lived in the UK for the last 3 years
Applicants need to have achieved GCSE mathematics and English (or equivalent) at grade 4 or above which is equivalent to a C grade as well as having completed at least 1 Numerical or Science based Level 3 or above qualification. Candidates will also need to be predicted or already have achieved 120 UCAS points at A Level (this would be equivalent to BBB) or hold a recognised and equivalent qualification.
OR
Applicants must have completed a Level 3 data related apprenticeship or actuarial/professional qualification or Bachelor's Degree in a Numerical or Science based subject / Economics subject (typically any data related degree would unfortunately make you ineligible.) If you have studied a non-Numerical or Science based Bachelor's degree, you need to have also completed a Numerical or Science based further education qualification and achieved 120 UCAS points.
Training Provided:
By becoming an apprentice at DLG, you'll be able to combine on-the-job practical skills with theoretical knowledge from off-the-job learning, giving you the best opportunity to develop your career in the insurance industry.
You will be paired with a dedicated DLG mentor who you will report into, they will support your training every step of the way by providing tailored coaching and support.
You will attend both online and face-to-face learning support sessions and there is an End-Point-Assessment for this apprenticeship where you will demonstrate your knowledge, skills, and behaviours.
Subject to successful completion of the apprenticeship, there are many opportunities for progression throughout DLG to continue your career with us.
What we'll give you in addition:
We wouldn't be where we are today without our people and the wide variety of perspectives and life experiences they bring. That's why we offer excellent benefits to suit your lifestyle and a flexible working model combining the best parts of home and office-working, varying with the nature of your role.
Core benefits include:
9% employer contributed pension
50% off home, motor and pet insurance plus free travel insurance and Green Flag breakdown cover
22 days holiday (rising by 1 day each year to 25) + bank holidays and option to buy or sell up to 5 days
Additional optional health and dental insurance
Buy as you earn share scheme
Employee discounts and cashback
Plus many more
Ways of Working:
Our mixed model way of working offers a 'best of both worlds' approach combining the best parts of home and office-working, offering flexibility for everyone. How much you'll be in the office depends on your role, and we'll consider the flexible working options that work best for you.
Read our flexible working approach here.
There's no-one else like you. No-one with the exact same mix of strengths, quirks, skills and thoughts. That's why you could belong here. As part of a team of brilliant individuals, in a place that empowers you to be the best you can be. We're proud of who we are, of what we do, and what every single one of us brings. Join us. Help us keep innovating and putting customers at the heart of everything. To be an insurance company of the future. When we work together, we can all achieve great things. Inspiring, challenging, and supporting each other to aim higher.
Being yourself:
Direct Line Group is an equal opportunity employer, and we think diversity of background and thinking is a big strength in our people. We're delighted to feature as one of the UK's Top 50 Inclusive Employers and are committed to making our business an inclusive place to work, where everyone can be themselves and succeed in their careers.
We know you're more than a CV, and the things that make you, you, are what bring potential to our business. We recognise and embrace people that work in different ways so if you need any adjustments to our recruitment process, please speak to the recruitment team who will be happy to support you.
Together we're one of a kind.
Please contact earlycareers@directlinegroup.co.uk if you have any questions.
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