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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 28800 - 48000 £ per year.
The ideal candidate's favorite 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: LinkedIn
Contact Detail:
LinkedIn 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 modelling 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 specific Big Data frameworks mentioned in the job description, like Hadoop and Spark. Having a solid grasp of these tools can set you apart from other candidates and show your commitment to the role.
✨Tip Number 4
Prepare to discuss how you generate actionable insights from data. Think of examples where your analysis led to significant business improvements, as this will highlight your ability to turn data into valuable outcomes.
We think you need these skills to ace Científico de datos
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in quantitative analytics and data modelling. Emphasise your skills in predictive modelling, machine learning, and any relevant programming languages like Python or SQL.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data and learning. Mention specific projects where you've successfully analysed complex data sets and how you collaborated with teams to implement solutions.
Showcase Relevant Experience: When detailing your work experience, focus on your achievements in data analysis and algorithm design. Use metrics to demonstrate the impact of your work, such as improvements in efficiency or accuracy.
Prepare for Technical Questions: Be ready to discuss your technical skills and experiences during the interview process. Brush up on your knowledge of big data frameworks and visualisation tools, as well as your understanding of clustering and classification techniques.
How to prepare for a job interview at LinkedIn
✨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.
✨Demonstrate Collaboration
Since collaboration with the engineering team is key, think of instances where you've worked in a team setting. Highlight how you communicated your findings and how you contributed to bringing analytical prototypes to production.
✨Brush Up on Technical Skills
Make sure you're comfortable discussing the programming languages and frameworks mentioned in the job description. Be ready to answer technical questions or even solve problems on the spot to showcase your fluency in Python, SQL, or any other relevant tools.
✨Prepare Insightful Questions
At the end of the interview, you'll likely have the chance to ask questions. Prepare thoughtful queries about the company's data strategy, the tools they use, or how they measure success in data-driven projects. This shows your genuine interest in the role and the company.
