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- Tasks: Develop reliable data tools and statistical models for sports advisory.
- Company: Dynamic sports advisory business with a focus on innovation.
- Benefits: Competitive salary, flexible hours, and holiday buyback scheme.
- Why this job: Join a remote team and make an impact in the sports industry.
- Qualifications: Master’s degree in STEM and strong skills in Python and SQL.
- Other info: Collaborative environment with opportunities for professional growth.
The predicted salary is between 36000 - 60000 £ per year.
A sports advisory business is looking for a full-stack Data Scientist to develop reliable data tools and statistical models. This primarily remote position emphasizes collaboration with engineers and client teams, offering competitive salary, flexible hours, and a holiday buyback scheme.
Ideal candidates should have a Master’s degree in a STEM field, and strong skills in Python and SQL. The role includes building analysis pipelines and contributing to production workflows.
Remote Data Scientist - Full-Stack ML & Production Tools in London employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote Data Scientist - Full-Stack ML & Production Tools in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the sports advisory and data science fields on LinkedIn. A friendly message can go a long way, and you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data tools and statistical models. Use platforms like GitHub to share your projects, especially those involving Python and SQL, so potential employers can see what you bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Practice coding challenges and be ready to discuss your experience with building analysis pipelines. We want you to feel confident when it’s time to shine!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Remote Data Scientist - Full-Stack ML & Production Tools in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python and SQL skills in your application. We want to see how you’ve used these tools in real projects, so don’t hold back on the details!
Tailor Your Application: Take a moment to customise your CV and cover letter for this role. Mention your experience with data tools and statistical models, as it’ll show us you’re a perfect fit for our team.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication, so avoid jargon unless it’s necessary to showcase your expertise.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Jobster
✨Know Your Tech Stack
Make sure you brush up on your Python and SQL skills before the interview. Be ready to discuss specific projects where you've used these languages, as well as any libraries or frameworks that are relevant to data science.
✨Showcase Your Collaboration Skills
Since this role involves working closely with engineers and client teams, prepare examples of how you've successfully collaborated in the past. Highlight any experiences where you’ve contributed to team projects or worked cross-functionally.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your analytical thinking and problem-solving abilities. Practice explaining your thought process when tackling data-related challenges, and be ready to walk through your approach to building analysis pipelines.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and the role. Inquire about their current data tools, the types of projects you might work on, or how they measure success in this position.
