Senior Insights Lead for Client Analytics & AI (12m) in London

Senior Insights Lead for Client Analytics & AI (12m) in London

London Temporary 47250 - 57750 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Deliver top-notch insights and lead tailored solutions for clients.
  • Company: Join Reward, a leading insight business with a strong reputation.
  • Benefits: Gain valuable experience in a dynamic environment with potential for growth.
  • Other info: 12-month maternity cover role with opportunities to shine.
  • Why this job: Be the go-to expert and make a real impact on client success.
  • Qualifications: Experience in insights and strong communication skills required.

The predicted salary is between 47250 - 57750 £ per year.

Reward is seeking an Insight Manager (12 months - Maternity Cover) to join the Insight Solutions group. You will deliver accurate and timely best-in-class insights to clients, and lead configurable solutions to meet client needs. You will be a go-to insight expert for account management and sales teams. You will engage directly with top clients, helping build Reward’s reputation as a leading insight business, ensuring clients can act confidently with our insights and addressing complex issues.

Senior Insights Lead for Client Analytics & AI (12m) in London employer: Reward

Reward is an exceptional employer that prioritises innovation and employee development within the dynamic field of customer engagement. With a strong commitment to work-life balance, flexible working arrangements, and a supportive culture, employees are empowered to thrive while contributing to meaningful client solutions. The company also offers competitive benefits, including pension contributions and family-friendly policies, making it an attractive place for professionals seeking growth and impact in their careers.

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Contact Details:

Reward Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Insights Lead for Client Analytics & AI (12m) in London

Tap into Online Data Science Communities

Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Reward before they're even advertised!

Show Off Your Skills With Projects

Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.

Check Out Specialist Job Boards

For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like Reward.

Leverage University Resources

If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like Reward.

We think you need these skills to ace Senior Insights Lead for Client Analytics & AI (12m) in London

Insight Delivery
Client Engagement
Account Management
Sales Support
Analytical Skills
Problem-Solving Skills
Communication Skills

Some tips for your application 🫡

Highlight Your Data Projects:When applying for a temporary data science role at Reward, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.

Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!

Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Reward, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.

Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Reward’s attention and show the tangible impact of your work.

How to prepare for a job interview at Reward

Showcase Your Analytical Skills

For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Reward.

Brush Up on Technical Skills

You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.

Highlight Your Adaptability

Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Reward.

Prepare a Portfolio of Your Work

Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Reward.