At a Glance
- Tasks: Lead a team to solve complex business problems using advanced analytics and predictive modelling.
- Company: Join a collaborative company that inspires progress and innovation.
- Benefits: Competitive salary, professional development, and a supportive work environment.
- Other info: Opportunity to mentor and grow within a dynamic team.
- Why this job: Make a real impact by enabling possibilities through data-driven insights.
- Qualifications: Experience in advanced analytics, particularly in the insurance industry, is essential.
The predicted salary is between 60000 - 72000 £ per year.
With a company culture rooted in collaboration, expertise and innovation, we aim to promote progress and inspire our clients, employees, investors and communities to achieve their greatest potential.
Our work is the catalyst that helps others achieve their goals.
In short, We Enable Possibility℠.
- Job Responsibilities
- Work closely with business partners to understand the business problems they are trying to solve and help develop and prioritize the best‑suited analytics solutions.
- Collaborate in cross‑functional teams and share ideas to solve complex business problems.
- Build strong partnerships with peers across the organization to support project goals and border team needs.
- Oversee the build of predictive models using advanced analytics techniques including GLMs, GBMs, natural language processing and other machine learning approaches.
- Develop powerful insights using a variety of analytical tools, techniques, and technologies, and deliver results into the business which drive business decisions.
- Discover, explore and analyse internal and external datasets for the purpose of developing advanced analytics models.
- Help establish best practices and repeatable processes for the Strategic Analytics team.
- Provide thought leadership on new, innovative techniques, approaches and software.
- Guide, support, mentor and develop the growing team of predictive modelers and data scientists.
- Desired Skills/Experience
- Ability to design, build and implement statistical models, with an understanding of a range of analytical techniques such as predictive modelling, NLP and data mining.
- Data manipulation and analytical skills in languages such as Python and SQL.
- Knowledge of modern visualization tools such as Power BI is a plus.
- Familiarity with cloud‑based platforms such as Databricks, Snowflake and Azure is an advantage, but not essential.
- Effective task / project management and general organization skills.
- Excellent verbal and written communications skills; ability to convey complex concepts to technical and non‑technical people across the organization.
- Exceptional teamwork skills required to play a key role in cross‑functional teams. Ability to collaborate and build trusting relationships with business partners.
- Natural curiosity to understand the world around you and question as needed.
- Comfortable handling ambiguous concepts and breaking down complex problems into manageable pieces.
- Ability to apply critical thinking and creative problem‑solving skills.
- Required Skills/Experience
- Experience in advanced analytics roles, a significant portion of which should be in the insurance industry.
- Experience working in an analytical role within a London Market insurance environment is an significant advantage.
- Hands‑on experience developing and deploying real‑time predictive models in the London Market.
- Experience delivering business value from small or non‑standard data sets.
Education
- Degree in statistics, mathematics, computer science, engineering or similar quantitative fields; or significant experience in advanced data analytics.
- 14101 Arch Europe Insurance Services Ltd
- #J-18808-Ljbffr
Data Science Manager employer: Arch Insurance Group Inc.
At Arch Insurance UK, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to reach their full potential. As a Senior PMO, you will be part of a dynamic team dedicated to driving transformation within the London Market, with ample opportunities for professional growth and development. Our commitment to excellence not only enhances your career but also contributes to meaningful outcomes for our clients and communities.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Manager
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Arch Insurance Group Inc.!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Science Manager at Arch Insurance Group Inc..
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Arch Insurance Group Inc..
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We think you need these skills to ace Data Science Manager
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 Arch Insurance Group Inc., 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 Arch Insurance Group Inc.. 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 Arch Insurance Group Inc.
✨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 Arch Insurance Group Inc.!
✨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.
