At a Glance
- Tasks: Lead data science projects and turn complex data into actionable insights.
- Company: Exciting fashion retail brand in vibrant Central London.
- Benefits: Flexible work with 2 days in the office, competitive salary, and growth opportunities.
- Other info: Diverse and inclusive workplace encouraging applications from all backgrounds.
- Why this job: Join a dynamic team and make a real impact in the fashion industry.
- Qualifications: 6+ years experience with Python, R, or SQL and strong analytical skills.
An exciting fashion retail brand in London is looking for an Analytics Manager to join their growing data team.
2 days a week in the office - Central London
As the Analytics Manager, your responsibilities will include:
- Partnering with Marketing and Buying/Merchandising teams to support brand and trading goals
- Delivering and evaluating data science projects (e.g. random forest, k-means, linear regression)
- Enhancing existing data sets through data mining
- Turning complex data into clear, actionable business insights
6+ years' experience with tools like Python, R or SQL
- Proven ability to lead analytics projects end to end
- Passionate about improving data quality and tool adoption across the business
- Experienced in analytical modelling and machine learning techniques
You can apply for the Analytics Manager position now by sending us your CV or by calling us!
We encourage applications regardless of ethnic origin, race, religious beliefs, age, disability, gender or sexual orientation, and any other protected status as required by applicable law.
Sphere Digital Recruitment is acting as an Employment Business in relation to this vacancy.
Analytics Director - Data Science in London employer: Sphere Digital Recruitment
As a leading player in the GRC and Risk sector, our company offers an exceptional work environment that fosters collaboration and innovation. With a strong focus on employee growth, we provide ample opportunities for career advancement while supporting a hybrid working model from our vibrant London office. Join us to be part of a dynamic team where your contributions are valued, and you can truly shape your success.
Contact Details:
Sphere Digital Recruitment Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Director - Data Science in London
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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!
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Craft a Tailored Cover Letter:For a full-time role at Sphere Digital Recruitment, 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 Sphere Digital Recruitment. 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 Sphere Digital Recruitment
✨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!
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✨Get Comfortable with Python and R
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✨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.
