At a Glance
- Tasks: Lead a team of data scientists to drive analytics for merchant growth and operations.
- Company: Join Deliveroo, a leading food delivery service with a dynamic team in London.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Fast-paced environment with collaboration across multiple teams.
- Why this job: Make a real impact on merchant success and shape the future of food delivery.
- Qualifications: Experience in data science and leadership skills are essential.
The predicted salary is between 70000 - 85000 £ per year.
Deliveroo is hiring a Data Science Manager to lead the Merchants team in London. You will guide a group of 4–7 data scientists and drive analytics that shape merchant acquisition, onboarding and retention, as well as merchant operations and self-serve tooling.
You will collaborate with Product, Engineering, Strategy, Operations and Commercial to align priorities, manage stakeholders and deliver high-impact, data-driven decisions in a fast-moving environment.
#J-18808-LjbffrMerchant Data Science Lead — Drive Growth & Partnerships employer: Stryker Corporation
Stryker Corporation is an exceptional employer that fosters a dynamic and inclusive work culture, offering employees the chance to thrive in a remote setting while being part of a leading medical communications team. With a strong emphasis on professional development and growth opportunities, employees are encouraged to enhance their skills and advance their careers, all while contributing to meaningful projects that impact healthcare globally.
StudySmarter Expert Advice🤫
We think this is how you could land Merchant Data Science Lead — Drive Growth & Partnerships
✨Get Involved in Data Science Meetups
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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 Stryker Corporation.
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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 Stryker Corporation, 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 Stryker Corporation. 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 Stryker Corporation
✨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.
