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- Tasks: Join us as a Data Scientist to shape our fashion discovery product using computer vision.
- Company: Hey Savi is a female-founded startup revolutionising online fashion shopping with data-driven solutions.
- Benefits: Enjoy flexible remote work, in-person team sessions, and a competitive contract rate of £300-£325 per day.
- Why this job: Make a significant impact in a supportive team while empowering others through fashion confidence.
- Qualifications: 3-4 years experience in data science, strong Python skills, and expertise in computer vision required.
- Other info: Passionate candidates who don't meet all criteria are encouraged to apply!
The predicted salary is between 60000 - 78000 £ per year.
About Hey Savi
We are a fully female-founded company on a mission to change the way people search and shop online for fashion. We aim to spark a new era of fashion discovery, igniting confidence in everybody and every body. Hey Savi is at the beginning of an exciting journey and we are looking for top talent to join our team. Data, specifically our data science models, are our intellectual property, so you will have a major role in shaping the product and experience.
About The Role
We are looking for an experienced Data Scientist specialising in Computer Vision to work with our Head of Data Science in building the engine that drives our product and experience. This is a pivotal role where the power of data, including Machine Learning and AI, will shape everything we do now and as we grow.
Requirements
- Must Haves:
- Experience: 3-4 years
- Education: Bachelor’s degree in relevant fields such as mathematics, data science, computer science or statistics
- Data: Great understanding and experience in handling image data and common analysis, enhancement and transformation techniques
- Computer Vision: Strong understanding of predictive techniques including neural network and transformer architectures
- Programming Skills: Strong Python programming skills and familiarity with cloud technologies
- Other: Good knowledge of best practices in MLOps
Nice to Haves:
- Education: MSc in relevant fields such as mathematics, data science, computer science or statistics
- Ability/experience in customising existing architectures to adapt to a specific use case
Complex Competencies:
- Intellectual Curiosity
- Flexible Thinking
- Collaboration
- Agility
- Independence
- Communication Skills
- Presentation Skills
- Organisation
Benefits
Location + Work Style: We will have in-person team sessions (usually once a week) as needed for key activities and remote work the rest of the time to allow for flexibility, work-life balance, and quiet time for deep work. Hey Savi is based in London and are looking for people in the UK and Europe to join our team. We regret that we can’t hire candidates from other locations or provide Visa sponsorship yet.
Contract Rate: £300-£325 per day
Data Scientist with Computer Vision employer: Hey Savi
Contact Detail:
Hey Savi Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist with Computer Vision
✨Tip Number 1
Familiarise yourself with the latest trends in computer vision and machine learning. Follow relevant blogs, attend webinars, and engage with communities on platforms like GitHub or LinkedIn to stay updated. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Showcase your hands-on experience with image data and deep learning models by working on personal projects or contributing to open-source initiatives. Having a portfolio that highlights your skills in object detection and classification can set you apart from other candidates.
✨Tip Number 3
Network with professionals in the data science and computer vision space. Attend industry meetups or conferences where you can connect with potential colleagues or mentors. Building relationships can lead to valuable insights and even job referrals.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and system design questions related to machine learning and MLOps. Use platforms like LeetCode or HackerRank to sharpen your skills, ensuring you're ready to tackle any technical assessments during the hiring process.
We think you need these skills to ace Data Scientist with Computer Vision
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and computer vision. Focus on specific projects where you've handled image data, trained models, or worked with cloud technologies like AWS.
Craft a Compelling Cover Letter: In your cover letter, express your passion for the mission of Hey Savi. Discuss how your skills align with their needs, particularly in areas like object detection, model evaluation, and collaboration with cross-functional teams.
Showcase Your Projects: If you have a portfolio or GitHub repository, include links to projects that demonstrate your expertise in computer vision and machine learning. Highlight any innovative solutions you've developed or contributed to.
Highlight Soft Skills: Since collaboration is key at Hey Savi, emphasise your communication skills and ability to work in a team. Provide examples of how you've successfully collaborated on projects or adapted to agile environments.
How to prepare for a job interview at Hey Savi
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and relevant libraries like TensorFlow and PyTorch. Bring examples of projects where you've successfully implemented computer vision techniques, especially in object detection and classification.
✨Understand the Company’s Mission
Research Hey Savi's mission to change the way people shop for fashion. Be ready to explain how your skills can contribute to their goals and how you align with their vision of empowering confidence through technology.
✨Demonstrate Collaboration Experience
Since you'll be working closely with a diverse team, share examples of past collaborations. Highlight your ability to communicate complex technical concepts to non-technical team members, showcasing your adaptability and teamwork.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, particularly in MLOps and model deployment. Think of scenarios where you've had to troubleshoot issues or optimise models, and be ready to discuss your thought process.
