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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 impactful projects in AI.
- Qualifications: Must be proficient in Python and familiar with machine learning libraries and frameworks.
- Other info: Stay updated with the latest AI advancements and collaborate with top professionals.
The predicted salary is between 36000 - 60000 £ 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.
Associate Data Scientist employer: Why Hiring
Contact Detail:
Why Hiring Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Associate Data Scientist
✨Tip Number 1
Familiarise yourself with the latest advancements in AI research. Follow relevant journals, blogs, and conferences 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 online. Join forums, attend webinars, or participate in hackathons. Networking with professionals can provide insights into the role and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your experience with specific libraries and frameworks mentioned in the job description. Be ready to share examples of projects where you've used tools like TensorFlow or PyTorch, as practical experience is key.
✨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 break down your work will be a valuable skill during interviews.
We think you need these skills to ace Associate Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the Associate Data Scientist role. Emphasise your proficiency in Python, experience with machine learning models, and familiarity with libraries like TensorFlow and PyTorch.
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 projects or experiences where you've utilised advanced AI features or worked with multimodal datasets.
Showcase Your Technical Skills: In your application, include examples of how you've used algorithms and libraries to solve complex problems. Discuss any relevant projects that demonstrate your ability to analyse extensive datasets and develop machine learning models.
Prepare for Technical Questions: Anticipate technical questions related to deep learning architectures and agile software development practices. Be ready to discuss your experience with code reviews, unit testing, and version control, as well as how you stay updated with AI advancements.
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 frameworks like TensorFlow or PyTorch, and be ready to explain your thought process and the challenges you faced.
✨Demonstrate Your Problem-Solving Ability
Expect to tackle some technical challenges during the interview. Practice explaining how you would approach complex problems using algorithms and machine learning models. Highlight your experience with both supervised and unsupervised learning.
✨Communicate Effectively
Since the role involves liaising with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Prepare to discuss how you've successfully communicated technical challenges and solutions in past experiences.
✨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 staying informed will demonstrate your passion for the field and your commitment to continuous learning.
