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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 field by integrating the latest AI 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 research. Follow relevant journals, blogs, and social media accounts 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 by participating in online forums or local meetups. Networking can lead to valuable connections and insights about the role, as well as potential referrals that could boost your application.
✨Tip Number 3
Work on personal projects that showcase your skills in Python and machine learning frameworks like TensorFlow or PyTorch. Having a portfolio of projects can set you apart from other candidates and provide concrete examples of your capabilities.
✨Tip Number 4
Prepare to discuss how you've tackled complex problems in past experiences. Be ready to explain your thought process and the algorithms you used, as this will highlight your problem-solving skills and technical expertise during interviews.
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, knowledge of machine learning frameworks, 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 libraries 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. Describe the challenges you faced, the solutions you implemented, and the outcomes. This will demonstrate your practical experience and problem-solving skills.
Prepare for Technical Questions: Anticipate technical questions related to machine learning models and algorithms. Be ready to discuss your experience with deep learning architectures and how you stay updated with AI advancements. This preparation will help you stand out 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 you've worked on that demonstrate your ability to utilise frameworks like TensorFlow or PyTorch.
✨Understand the Role of AI in Business
Research how AI solutions can solve real-world problems. Be ready to discuss how you would approach developing advanced AI features and the impact they could have on client challenges.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. You may need to communicate with both technical and non-technical stakeholders, so clarity is key.
✨Stay Updated on AI Trends
Familiarise yourself with the latest advancements in AI research. Being able to discuss recent developments will show your passion for the field and your commitment to continuous learning.
