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- Tasks: Work with data to create innovative AI solutions and tackle client challenges.
- 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 growth.
- Why this job: Be part of a team that values innovation and offers real-world impact through data science.
- Qualifications: Must know Python and have experience with AI libraries like TensorFlow and PyTorch.
- Other info: Stay ahead in the AI field by integrating the latest research into your work.
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, podcasts, and research papers to stay updated, as 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 sets you apart from other candidates.
✨Tip Number 3
Prepare to discuss your previous projects in detail, especially those involving multi-modal datasets or advanced AI features. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will highlight your problem-solving abilities.
✨Tip Number 4
Practice explaining complex technical concepts in simple terms. Since you'll need to communicate with both technical and non-technical stakeholders, being able to convey your ideas clearly will be a valuable asset 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 that showcase your ability to work with multimodal datasets.
Craft a Compelling Cover Letter: Write a cover letter that not only outlines your qualifications but also expresses your passion for data science and AI. Mention specific projects or experiences that demonstrate your ability to tackle complex challenges and your eagerness to contribute to Why Hiring's mission.
Showcase Your Technical Skills: In your application, include examples of your work with algorithms, libraries, and frameworks mentioned in the job description. If you have GitHub repositories or personal projects, link to them to provide evidence of your capabilities.
Prepare for Potential Interviews: While this step is more about preparation than writing, consider drafting responses to common interview questions related to data science and AI. This will help you articulate your thoughts clearly when discussing technical challenges and solutions during the interview process.
How to prepare for a job interview at Why Hiring
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in Python and the libraries mentioned in the job description. Bring examples of projects where you've used Hugging Face, TensorFlow, or PyTorch, and be ready to explain your thought process and the outcomes.
✨Demonstrate Your Problem-Solving Ability
Expect to face technical challenges during the interview. Practice explaining how you would approach complex problems using algorithms and machine learning models. Use real-world scenarios to illustrate your problem-solving skills.
✨Communicate Clearly
Since you'll need to communicate with both technical and non-technical stakeholders, practice explaining your work in simple terms. This will show that you can bridge the gap between different audiences and ensure everyone is on the same page.
✨Stay Updated on AI Trends
Research the latest advancements in AI and be ready to discuss how they could be integrated into the company's products. Showing that you're proactive about learning will demonstrate your passion for the field and your commitment to continuous improvement.
