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For Companies At a Glance
- Tasks: Analyse complex data, design prediction algorithms, and collaborate with engineers.
- Company: Join a forward-thinking company that values innovation and data-driven decisions.
- Benefits: Enjoy flexible working options and opportunities for professional growth.
- Why this job: Be part of a dynamic team that drives impactful business improvements through data insights.
- Qualifications: Bachelor's degree in a quantitative field and 1-2 years of relevant experience required.
- Other info: Fluency in programming languages and familiarity with Big Data tools is essential.
The predicted salary is between 30000 - 50000 £ per year.
The ideal candidate's favourite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.
Responsibilities
- Analyze raw data: assessing quality, cleansing, structuring for downstream processing
- Design accurate and scalable prediction algorithms
- Collaborate with engineering team to bring analytical prototypes to production
- Generate actionable insights for business improvements
Qualifications
- Bachelor's degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
- At least 1 - 2 years' of experience in quantitative analytics or data modeling
- Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms
- Fluency in a programming language (Python, C, C++, Java, SQL)
- Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau)
Científico de datos employer: Evertreen
Contact Detail:
Evertreen Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Científico de datos
✨Tip Number 1
Make sure to showcase your collaboration skills during the interview. Since the role involves working closely with the engineering team, be prepared to discuss past experiences where you successfully collaborated on data projects.
✨Tip Number 2
Brush up on your knowledge of predictive modeling and machine learning techniques. Be ready to explain how you've applied these concepts in real-world scenarios, as this will demonstrate your practical understanding of the field.
✨Tip Number 3
Familiarise yourself with the Big Data frameworks mentioned in the job description. If you have experience with tools like Hadoop or Spark, prepare to discuss specific projects where you utilised these technologies to extract insights from large datasets.
✨Tip Number 4
Be ready to talk about your programming skills, especially in Python or SQL. Consider preparing a small project or example that highlights your coding abilities and how they relate to data analysis and modelling.
We think you need these skills to ace Científico de datos
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in quantitative analytics and data modelling. Emphasise your skills in programming languages and any familiarity with Big Data frameworks, as these are crucial for the role.
Craft a Strong Cover Letter: In your cover letter, express your passion for data and learning. Mention specific projects where you've successfully analysed complex data sets or developed predictive algorithms, showcasing your collaboration skills.
Showcase Technical Skills: Clearly list your technical skills related to programming languages and data analysis tools. Provide examples of how you've used these skills in previous roles to generate actionable insights.
Prepare for Technical Questions: Anticipate technical questions related to predictive modelling and machine learning during the interview process. Brush up on key concepts and be ready to discuss your approach to solving data-related problems.
How to prepare for a job interview at Evertreen
✨Showcase Your Analytical Skills
Be prepared to discuss your experience with data analysis and predictive modelling. Bring examples of past projects where you successfully extracted insights from complex data sets, as this will demonstrate your ability to handle the responsibilities of the role.
✨Brush Up on Technical Knowledge
Make sure you're comfortable discussing programming languages like Python or SQL, as well as Big Data frameworks. You might be asked to solve a technical problem or explain a concept, so review key algorithms and techniques relevant to data science.
✨Emphasise Collaboration
Since the role involves working closely with engineering teams, highlight your collaboration skills. Share examples of how you've worked in teams to bring analytical prototypes to production, showcasing your ability to communicate effectively with different stakeholders.
✨Prepare Questions
Have insightful questions ready about the company's data strategy and how they leverage analytics for business improvements. This shows your genuine interest in the role and helps you assess if the company aligns with your career goals.
