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- Tasks: Develop data pipelines and machine learning models while optimising decision-support products.
- Company: Leading technology company with a focus on innovation and collaboration.
- Benefits: Flexible work environment and great potential for career advancement.
- Why this job: Join a dynamic team and make an impact with your data skills.
- Qualifications: Strong knowledge of machine learning, Python, SQL, and excellent communication skills.
- Other info: Exciting growth opportunities in a supportive and collaborative setting.
The predicted salary is between 30000 - 50000 £ per year.
A leading technology company is seeking a Data Scientist to develop data pipelines and machine learning models. This role involves working collaboratively within product squads and encompasses comprehensive responsibilities in optimizing decision-support products.
Candidates should have strong knowledge of machine learning techniques, be proficient in Python, SQL, and cloud platforms, and possess excellent communication skills.
This opportunity offers a flexible work environment and potential for career advancement.
Data Scientists — Flexible Work & Growth Opportunities employer: Amach
Contact Detail:
Amach Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientists — Flexible Work & Growth Opportunities
✨Tip Number 1
Network like a pro! Reach out to current Data Scientists or employees at the company you're eyeing. A friendly chat can give us insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and machine learning models. This is your chance to demonstrate your proficiency in Python, SQL, and cloud platforms.
✨Tip Number 3
Prepare for the interview by brushing up on your communication skills. Practice explaining complex concepts in simple terms, as collaboration is key in product squads.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed and shows you’re serious about joining the team.
We think you need these skills to ace Data Scientists — Flexible Work & Growth Opportunities
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data pipelines and machine learning models. We want to see how your skills in Python, SQL, and cloud platforms make you the perfect fit for our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're passionate about data science and how you can contribute to our product squads. Keep it engaging and personal – we love to see your personality!
Showcase Your Communication Skills: Since this role involves collaboration, it's crucial to demonstrate your communication skills in your application. Use clear and concise language, and don’t hesitate to share examples of how you've effectively communicated complex ideas in the past.
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’re considered for this exciting opportunity. Plus, it’s super easy!
How to prepare for a job interview at Amach
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of machine learning techniques, Python, SQL, and cloud platforms. Be ready to discuss specific projects where you've applied these skills, as this will show your practical experience and understanding.
✨Showcase Your Collaboration Skills
Since the role involves working within product squads, be prepared to share examples of how you've successfully collaborated with others in past projects. Highlight your communication skills and how they contributed to team success.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities. Practice explaining your thought process when tackling data-related challenges, and consider using the STAR method (Situation, Task, Action, Result) to structure your answers.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that demonstrate your interest in the company and the role. Inquire about the types of projects you might work on or how the team measures success in optimising decision-support products.
