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- Tasks: Work with cutting-edge algorithms to solve complex data challenges and develop AI features.
- Company: Join Why Hiring, a company dedicated to connecting talent with remote job opportunities.
- Benefits: Enjoy remote work flexibility and a culture that fosters creativity and career growth.
- Why this job: Be part of an innovative team that values your input and encourages professional development.
- Qualifications: Must be proficient in Python and familiar with machine learning libraries and frameworks.
- Other info: Stay updated with the latest AI advancements and apply them in real-world projects.
The predicted salary is between 28800 - 48000 £ per year.
At Why Hiring, we believe in the power of connecting talented individuals with incredible remote job opportunities. Our mission is to simplify the job search process and empower professionals to find fulfilling roles that align with their skills and passions, regardless of geographical constraints. In this role, you will collaborate with top-tier professionals in a setting that nurtures both creativity and career development. Engaging with multimodal datasets, you'll be instrumental in developing pioneering solutions on an extended roadmap.
Responsibilities:
- Utilize cutting-edge algorithms and libraries to address complex client challenges.
- Design and deploy advanced AI features.
- Analyze extensive multi-modal datasets to derive insights and features for downstream models and applications.
- Develop and refine traditional machine learning models for both supervised and unsupervised learning, as well as advanced AI models for tasks including image-to-text, text-to-image, question-answering, and summarization.
- Keep up-to-date with the latest advancements in AI research and integrate these into our products and services.
- Effectively communicate technical challenges and solutions to both technical and non-technical stakeholders and team members.
Qualifications:
- Proficiency in Python programming.
- Knowledge of agile software development practices, including code reviews, unit testing, and version control with git.
- Practical experience with libraries and frameworks such as Hugging Face, NLTK, SpaCy, TensorFlow, PyTorch, and Scikit-Learn.
- Strong grasp of deep learning architectures, including transformers, recurrent and convolutional neural networks, and attention mechanisms.
Junior Data Scientist employer: Why Hiring
Contact Detail:
Why Hiring Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior Data Scientist
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and machine learning. Follow relevant blogs, attend webinars, and participate in online courses to stay updated. This knowledge will not only help you in interviews but also demonstrate your passion for the field.
✨Tip Number 2
Engage with the data science community on platforms like GitHub or Kaggle. Contributing to open-source projects or participating in competitions can showcase your skills and provide practical experience that aligns with the responsibilities of the role.
✨Tip Number 3
Prepare to discuss your experience with specific libraries and frameworks mentioned in the job description. Be ready to explain how you've used them in past projects, as this will highlight your practical knowledge and problem-solving abilities.
✨Tip Number 4
Practice explaining complex technical concepts in simple terms. Since the role involves communicating with both technical and non-technical stakeholders, being able to articulate your ideas clearly will set you apart during the interview process.
We think you need these skills to ace Junior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the Junior Data Scientist role. Emphasise your proficiency in Python, experience with machine learning libraries, and any projects involving multimodal datasets.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your understanding of the company's mission. Mention specific algorithms or frameworks you have worked with and how they relate to the responsibilities outlined in the job description.
Showcase Your Projects: If you have completed any relevant projects, include them in your application. Provide links to your GitHub or portfolio where you demonstrate your ability to analyse datasets and develop machine learning models.
Prepare for Technical Questions: Anticipate technical questions related to algorithms, data analysis, and machine learning during the interview process. Brush up on your knowledge of deep learning architectures and be ready to discuss how you've applied them in past experiences.
How to prepare for a job interview at Why Hiring
✨Showcase Your Python Skills
As a Junior Data Scientist, proficiency in Python is crucial. Be prepared to discuss your experience with Python programming, including specific projects where you've used it to solve problems or analyse data.
✨Familiarise Yourself with AI Libraries
Make sure you know your way around libraries like TensorFlow, PyTorch, and Hugging Face. During the interview, mention any hands-on experience you have with these tools and how you've applied them in real-world scenarios.
✨Understand Agile Practices
Since the role involves agile software development, be ready to talk about your understanding of practices like code reviews and version control with git. Share examples of how you've implemented these in past projects.
✨Communicate Clearly
You'll need to explain complex technical concepts to both technical and non-technical stakeholders. Practice articulating your thoughts clearly and concisely, perhaps by explaining a project you've worked on to someone unfamiliar with data science.
