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- Tasks: Develop NLP models to analyse real-world data sets using cloud infrastructure.
- Company: Join a leading tech company at the forefront of innovation.
- Benefits: Enjoy flexible working options and a vibrant team culture.
- Why this job: Make an impact with cutting-edge technology in a collaborative environment.
- Qualifications: Proficient in Python and SQL, with a Master's in a numerate subject.
- Other info: Experience with Big Data and cloud services is essential.
The predicted salary is between 36000 - 60000 £ per year.
A leading technology company is looking for an experienced Data Scientist to join their growing and expanding data team. Your prime responsibility is to develop NLP models on cloud infrastructure to analyze real-world and unstructured data sets.
Candidate Requirements:
- Proficient in Python and SQL.
- Experience working in NLP.
- Masters in a highly numerate subject.
- Knowledge and working experience with Big Data technologies.
- Experience working with at least one cloud service provider (AWS, GCP, Azure).
NLP Data Scientist with Python and SQL employer: TN United Kingdom
Contact Detail:
TN United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land NLP Data Scientist with Python and SQL
✨Tip Number 1
Make sure to showcase your experience with NLP projects during networking events or meetups. Engaging with professionals in the field can lead to valuable connections and potential referrals.
✨Tip Number 2
Join online forums and communities focused on NLP and data science. Participating in discussions can help you stay updated on industry trends and may even lead to job opportunities through community members.
✨Tip Number 3
Consider contributing to open-source NLP projects on platforms like GitHub. This not only enhances your skills but also demonstrates your commitment and expertise to potential employers.
✨Tip Number 4
If you have experience with cloud services, be prepared to discuss specific projects where you've implemented these technologies. Real-world examples can set you apart during interviews and show your practical knowledge.
We think you need these skills to ace NLP Data Scientist with Python and SQL
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your proficiency in Python and SQL, as well as your experience with NLP. Include specific projects or roles where you've developed NLP models or worked with unstructured data.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and NLP. Mention your relevant qualifications, such as your Master's degree and any experience with Big Data technologies or cloud services like AWS, GCP, or Azure.
Showcase Relevant Projects: If you have worked on any notable projects involving NLP or cloud infrastructure, be sure to include them in your application. Describe the challenges you faced and how you overcame them, as this demonstrates your problem-solving skills.
Proofread Your Application: Before submitting your application, carefully proofread all documents for spelling and grammatical errors. A polished application reflects your attention to detail, which is crucial for a Data Scientist role.
How to prepare for a job interview at TN United Kingdom
✨Showcase Your NLP Knowledge
Be prepared to discuss your experience with Natural Language Processing. Highlight specific projects where you've developed NLP models, and be ready to explain the techniques and algorithms you used.
✨Demonstrate Python and SQL Proficiency
Since proficiency in Python and SQL is crucial for this role, brush up on your coding skills. You might be asked to solve a problem or write a query during the interview, so practice common data manipulation tasks.
✨Familiarise Yourself with Cloud Technologies
As the role involves working on cloud infrastructure, make sure you understand the basics of at least one cloud service provider like AWS, GCP, or Azure. Be ready to discuss how you've used these platforms in past projects.
✨Prepare for Big Data Discussions
Knowledge of Big Data technologies is essential. Be prepared to talk about your experience with tools like Hadoop or Spark, and how you've handled large datasets in your previous roles.
