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- Tasks: Join our team to develop analytics solutions for non-life insurance using Python and R.
- Company: LCP is a top consultancy blending analytics with human expertise for a better future.
- Benefits: Enjoy 26 days of leave, private medical insurance, and professional study support.
- Why this job: Be part of a fun, collaborative team that values personal and professional growth.
- Qualifications: Experience in Python and analytics; knowledge of insurance is a plus.
- Other info: We promote diversity and inclusivity, welcoming applicants from all backgrounds.
The predicted salary is between 36000 - 60000 £ per year.
LCP is a leading independent consultancy that uses powerful analytics fused with human expertise to shape a more positive future. We provide market-leading capabilities across pensions and financial services, energy, health, and analytics. Our technology and analytics capabilities are fundamental to what we do, helping us power the possibilities that provide solutions for tomorrow. We strive to help our clients leverage the latest technology and analytics across a range of industries to stay at the forefront of data-driven and digital solutions.
Within the Insurance Analytics team we are passionate about applying the latest analytics techniques to actuarial work and are keen to work with people who share our passion. Our market leading analytics platform, LCP InsurSight, was launched in April 2020, and is used by some of the largest insurers in the world to assess over £150bn reserves.
Some of the things we have done so far include:
- Using machine learning to automatically identify and highlight trends in insurers’ data and deploying this to production in InsurSight using Azure
- Analysis to assess the impact of key factors including weather, age of vehicle and driver region on the reserves of a large UK motor insurer
- Building stochastic simulation models in R to support one of the largest reinsurance placements in the London Market
What’s the role and what will you be doing?
Due to the success of the team, we are looking for someone to help us develop LCP InsurSight further and deliver more consulting analytics projects to insurers. We are looking for individuals with experience in delivering analytics projects to non-life insurers in Python. Experience with R and/or working with cloud computing (preferably Azure) would be beneficial but is not essential.
Specifically, you will be:
- Working within our dynamic team of actuaries, data scientists and software developers
- Using your insurance, data science and actuarial knowledge to design and implement analytics solutions to non-life insurance problems, using modern techniques whilst considering practicalities such as the amount of data available and explicability
- Working on the development and implementation of new features in InsurSight, including delegating work to more junior members of the team. Day to day, this will involve writing and reviewing Python code in Pycharm, using version control, writing tests, and deploying code to production in Azure
- Developing prototypes of new analytics solutions and supporting the wider Insurance Consulting team in using these solutions in consultancy projects (e.g., new analytics solutions, analysing large datasets and building automated processes)
- Working on consulting projects, primarily those requiring Python and/or analytics techniques, but also occasionally working on broader projects where necessary, these projects would be across pricing, reserving, capital and claims
- Training more junior members of the team in Python and applying statistical and machine learning techniques to solve business problems effectively
- Planning and executing work in reasonable timescales to stipulated or agreed deadlines
- Checking work you have completed, and/or reviewing work completed by more junior members of the team, including performing reasonableness checks using your knowledge of non-life insurance and actuarial work
- Working within LCP’s internal professional standards and external professional guidance
What are we looking for?
- To transform actuarial work you need to have a good understanding of the work actuaries do for insurers, you don’t have to be an actuary though!
- You’re happy working in Python, ideally you have significant experience using Pandas in Python. Experience using R and R’s Tidyverse packages would be beneficial but is not essential.
- Track record of applying statistical and machine learning techniques to solve business problems for non-life insurers
- Experience working in a controlled coding environment, including using version control and a testing framework
- Excellent presentation and communication skills, able to give concise summaries of analytics solutions, but also comfortable answering detailed technical questions
What’s in it for you?
Take a look at our Glassdoor page to see why our people love being here! As well as joining a multi-award winning, fun, collaborative, people-first organisation where your personal and professional skills will be developed to make you the best you can be, we offer an attractive benefits package designed to promote your overall wellbeing so that you are able to perform to your full potential both in and out of work. Currently, our core benefits package includes:
For you:
- Professional study support (where applicable)
- Access to our internal Wellbeing, LGBTQ+, Multicultural and Women’s networks
For your family:
- Life assurance
- Income protection
- Enhanced maternity/paternity/adoption and shared parental leave
For your health:
- 26 days annual leave (pro-rata for part-time working) plus bank holidays (most of which can be taken flexibly!) with options to buy & sell holiday
- Private medical insurance
- Discounted gym memberships, critical illness and dental insurance through our flexible benefits
- Cycle to work scheme
- Digital GP services
For your wealth:
- Discretionary bonus scheme
- Season ticket loans
For others:
- Volunteering opportunities
For the environment:
- Electric vehicle salary sacrifice scheme (qualifying period applies)
And much more!
We continuously strive to build an inclusive workplace where all forms of diversity are valued, including age, background, disability, gender, gender identity, gender expression, race, religion or sexual orientation.
LCP is committed to making our opportunities accessible to all and would welcome you getting in touch to let us know if an adjustment can be made to help with your application. This may be extra time for assessments, pre-interview site visits, interview structure or questions, or asking us about building accessibility. Whatever it may be, please get in touch via our dedicated email address – to discuss how we can support you with your application.
LCP currently holds a sponsorship license for skilled worker visas, allowing us to assist with applications aligning with the UK Government’s criteria for skilled worker sponsorship. If you anticipate needing sponsorship for a skilled worker visa, we recommend reviewing the sponsorship criteria for your desired role before applying to LCP.
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Actuarial Data Scientist employer: Lane Clark & Peacock LLP.
Contact Detail:
Lane Clark & Peacock LLP. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Actuarial Data Scientist
✨Tip Number 1
Familiarize yourself with LCP InsurSight and its features. Understanding how this analytics platform works will give you an edge in interviews, as you can discuss how your skills in Python and data science can contribute to its development.
✨Tip Number 2
Brush up on your knowledge of non-life insurance and actuarial principles. Being able to speak confidently about these topics will demonstrate your understanding of the industry and how your background aligns with the role.
✨Tip Number 3
Showcase any experience you have with machine learning techniques and statistical analysis. Prepare examples of past projects where you've applied these skills, especially in a controlled coding environment, as this is crucial for the position.
✨Tip Number 4
Network with current or former employees of LCP if possible. They can provide insights into the company culture and expectations, which can help you tailor your approach during the application process.
We think you need these skills to ace Actuarial Data Scientist
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Actuarial Data Scientist position. Familiarize yourself with the tools and technologies mentioned in the job description, such as Python, R, and Azure.
Tailor Your CV: Customize your CV to highlight relevant experience in analytics projects, particularly those related to non-life insurance. Emphasize your proficiency in Python and any experience with machine learning techniques, as well as your ability to work in a team.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for analytics and actuarial work. Mention specific projects or experiences that align with LCP's goals and values, and express your enthusiasm for contributing to the development of LCP InsurSight.
Highlight Communication Skills: Since excellent presentation and communication skills are essential for this role, provide examples in your application that demonstrate your ability to explain complex analytics solutions clearly and concisely, both in writing and verbally.
How to prepare for a job interview at Lane Clark & Peacock LLP.
✨Showcase Your Python Skills
Since the role heavily involves Python, be prepared to discuss your experience with it in detail. Highlight specific projects where you've used Python, especially with libraries like Pandas, and be ready to demonstrate your coding skills if asked.
✨Understand Actuarial Concepts
Even though you don't need to be an actuary, having a solid understanding of actuarial work is crucial. Brush up on key concepts related to non-life insurance, such as pricing, reserving, and claims, so you can speak confidently about how analytics can solve these problems.
✨Prepare for Technical Questions
Expect detailed technical questions regarding statistical and machine learning techniques. Be ready to explain how you've applied these methods in past projects, and think of examples that showcase your problem-solving abilities in a controlled coding environment.
✨Demonstrate Team Collaboration
The role involves working within a dynamic team, so emphasize your teamwork skills. Share experiences where you've collaborated with others, mentored junior members, or contributed to group projects, highlighting your ability to communicate complex ideas clearly.
