At a Glance
- Tasks: Lead the development of advanced analytics and measurement methodologies in a dynamic team.
- Company: SMG, a forward-thinking company based in London or Nottingham.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Join a collaborative environment with exciting projects and career advancement potential.
- Why this job: Make a real impact by transforming data into actionable insights and leading a talented team.
- Qualifications: Experience in data science, strong analytical skills, and leadership capabilities.
The predicted salary is between 60750 - 74250 £ per year.
SMG in London or Nottingham is seeking a Senior Data Scientist to lead the technical development of our measurement and advanced analytics capability.
You will craft robust methodologies and models across retail media networks, while guiding a small team of analysts and data scientists.
You will design, code, test, and validate analytical solutions, partnering with Data Engineering, Platform and Product to transform methodologies into production-ready systems.
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Senior Data Scientist & Analytics Lead (Hybrid) employer: Capture
At SMG, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to excel. As a Senior Data Scientist in our London or Nottingham office, you will benefit from a hybrid working model, competitive remuneration, and opportunities for professional growth within a dynamic team dedicated to pushing the boundaries of analytics in retail media. Join us to make a meaningful impact while enjoying a supportive environment that values your contributions and encourages continuous learning.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist & Analytics Lead (Hybrid)
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We think you need these skills to ace Senior Data Scientist & Analytics Lead (Hybrid)
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 Capture, 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 Capture. 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 Capture
✨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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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
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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.
