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- Tasks: Lead data science projects and communicate results to senior management.
- Company: Join a dynamic life insurance company focused on innovative data solutions.
- Benefits: Enjoy flexible work options and opportunities for professional growth.
- Why this job: Make a real impact by driving strategic initiatives with data analytics.
- Qualifications: 5-7 years in data science, preferably in insurance or financial services.
- Other info: Work permit may be required for non-citizens.
The predicted salary is between 43200 - 72000 £ per year.
The core duties of the role involve building and submitting a range of data science solutions aligned to the wider business strategy. It would suit an individual with a quantitative background who is looking to broaden their commercial experience within a life insurance setting.
Working within a multi-stakeholder framework including Business Solutions, Distribution Channels, Marketing and Actuarial, the candidate will take responsibility for a number of end-to-end processes and communication of results to senior management from an early stage. The candidate will be required to work flexibly across a range of other projects, covering areas such as data analytics and proposition development, providing the candidate with a breadth and depth of strategic initiatives.
In addition, the candidate will be required to lead the development of data science applications, such as within Python, SQL and PowerBI, to implement and improve processes with large sets of data to provide MI and inputs into the strategic steer of the company.
Key Responsibilities and Duties
- Identify areas to apply data science, both in terms of new growth opportunities and in-force optimisation.
- Perform investigations using data science applications and present the results in an appropriate way for a range of stakeholders.
- Responsible for the training of the Machine Learning models such as propensity models.
- Integrate CRM with Machine Learning models to perform effective data analysis.
- Accountable for building predictive modelling solutions that can be rolled out to actionable initiatives across the business.
- Support the ongoing management of the business by considering opportunities around data strategy.
- Work closely with distribution channels to support performance management using data analytics, such as identifying trends and customer behaviour.
- Ensure the data analysis complies with internal and external requirements such as Group AI Policy, Consumer Duty and other regulatory requirements.
Skills and Experience
- Background in computer science, mathematics/statistics with hands-on quantitative experience, ideally 5 – 7 years.
- Experience working in an insurance company setting or any other financial service is preferred.
- Familiarity with data science software such as Python, R, SPSS Modeller.
- Experience in using one of Power BI, Tableau or Qlik.
- Ability to build Machine Learning models from scratch with good documentation and governance.
- Demonstrable strong communication and relationship management skills.
- Ability to explain technical subjects to senior stakeholders both written and verbally.
Please note that if you are NOT a passport holder of the country for the vacancy, you might need a work permit.
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Data Science Manager employer: TN United Kingdom
Contact Detail:
TN United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager
✨Tip Number 1
Familiarize yourself with the specific data science applications mentioned in the job description, such as Python, SQL, and Power BI. Consider working on personal projects or contributing to open-source projects that showcase your skills in these areas.
✨Tip Number 2
Network with professionals in the insurance and financial services sectors. Attend industry events or join relevant online communities to connect with potential colleagues and learn more about the challenges they face, which can help you tailor your approach during interviews.
✨Tip Number 3
Prepare to discuss your experience with predictive modeling and machine learning in detail. Be ready to share specific examples of how you've built models from scratch and the impact they had on previous projects or businesses.
✨Tip Number 4
Practice explaining complex technical concepts in simple terms. Since you'll be communicating with senior stakeholders, being able to convey your findings clearly and effectively will be crucial for your success in this role.
We think you need these skills to ace Data Science Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your quantitative background and relevant experience in data science, particularly in the insurance or financial services sector. Emphasize your skills in Python, SQL, and Power BI.
Craft a Strong Cover Letter: In your cover letter, explain how your experience aligns with the responsibilities of the Data Science Manager role. Mention specific projects where you've successfully applied data science solutions and how they contributed to business strategy.
Showcase Communication Skills: Since the role requires explaining technical subjects to senior stakeholders, include examples in your application that demonstrate your strong communication and relationship management skills.
Highlight Leadership Experience: If you have experience leading projects or teams, make sure to highlight this in your application. Discuss how you've trained others or led the development of data science applications, as this is crucial for the role.
How to prepare for a job interview at TN United Kingdom
✨Showcase Your Technical Skills
Be prepared to discuss your experience with data science applications like Python, SQL, and PowerBI. Highlight specific projects where you've built predictive models or integrated machine learning into business processes.
✨Understand the Business Context
Research the life insurance industry and understand how data science can drive growth and optimize existing processes. Be ready to discuss how your skills can align with the company's strategic initiatives.
✨Communicate Effectively
Practice explaining complex technical concepts in simple terms. You’ll need to present findings to senior management, so focus on clarity and relevance when discussing your past work and its impact.
✨Prepare for Stakeholder Engagement
Think about how you would engage with various stakeholders, from marketing to actuarial teams. Be ready to share examples of how you've collaborated across departments to achieve common goals.
