Senior Insight & Sponsorship Research Executive

Senior Insight & Sponsorship Research Executive

Full-Time 35000 - 42000 £ / year (est.) Home office (partial)
MLS Talent

At a Glance

  • Tasks: Design and deliver research projects, analyse data, and present insights to clients.
  • Company: MLS Talent, a dynamic company at the intersection of sports and culture.
  • Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Join a vibrant team and make a real difference in the industry.
  • Why this job: Turn data into impactful stories and contribute to exciting business strategies.
  • Qualifications: 2-4 years of quantitative research experience and a passion for sports.

The predicted salary is between 35000 - 42000 £ per year.

MLS Talent is seeking a Senior Research & Insight Account Executive in London (Hybrid). This role is a fantastic opportunity for individuals with a strong background in quantitative research and a passion for sports and culture.

The successful candidate will design and deliver research projects, analyze data, and present insights to clients, contributing significantly to business pitches and strategies.

If you have 2–4 years of relevant experience and are eager to turn data into impactful stories, apply now!

Senior Insight & Sponsorship Research Executive employer: MLS Talent

MLS Talent is an exceptional employer that fosters a dynamic and inclusive work culture, where creativity and collaboration thrive. With a strong emphasis on employee growth, we offer tailored development opportunities and the chance to work on exciting projects in the vibrant city of London. Join us to turn your passion for sports and culture into meaningful insights while enjoying the benefits of a hybrid working model.

MLS Talent

Contact Details:

MLS Talent Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Insight & Sponsorship Research Executive

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 MLS Talent!

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 Senior Insight & Sponsorship Research Executive at MLS Talent.

Leverage Professional Networks

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 MLS Talent.

Apply Directly through Our Website

When you find a suitable opening like Senior Insight & Sponsorship Research Executive at MLS Talent, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Senior Insight & Sponsorship Research Executive

Quantitative Research
Data Analysis
Presentation Skills
Client Engagement
Business Strategy Development
Research Project Design
Insight Generation

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 MLS Talent, 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 MLS Talent. 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 MLS Talent

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 MLS Talent!

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.