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- Tasks: Lead a team to innovate in data processing and machine learning for Amazon's product selection.
- Company: Join Amazon, a global leader in e-commerce and technology, shaping the future of shopping.
- Benefits: Enjoy flexible work options, competitive pay, and a vibrant company culture.
- Why this job: Make a real impact by solving complex problems and collaborating with diverse tech teams.
- Qualifications: 3+ years in management with expertise in ML, NLP, and analytics required.
- Other info: Inclusive workplace with support for all applicants, ensuring equal opportunities.
The predicted salary is between 48000 - 72000 £ per year.
Manager, Applied Science, Selection Monitoring
The Amazon Selection and Catalog Systems team (ASCS) builds global selection and catalog management systems. The Selection Monitoring team is responsible for building the biggest product selection on the planet to satisfy our customers’ all shopping needs. We build platforms, systems and tools to create and take advantage of datasets that contains billions of records, use the latest machine learning, data processing technologies and a broad set of AWS technologies. In order to drive the expansion of Amazon selection, we use cluster-computing technologies such as MapReduce and Spark to process billions of products and find the products/brands not already sold on Amazon. We work with structured and unstructured content such as text and images and apply Machine Learning algorithms such as Clustering, Natural Language processing, Fuzzy matching and Image processing at a massive scale.
We are looking for a Manager, Applied Science to tackle ambiguous problems in the areas of data processing, machine learning algorithms and distributed systems of cloud-scale. You are expected to take ownership, dive deep and drive solutions from developing prototypes, doing experiments, design to coding, testing and deployment. The role demands innovation and expects you to push the boundaries. You will get opportunity to work with many tech teams and business teams within Amazon and deliver solutions that will have an impact to both Amazon top-line & bottom line.
BASIC QUALIFICATIONS
– 3+ years of scientists or machine learning engineers management experience
– Knowledge of ML, NLP, Information Retrieval and Analytics
PREFERRED QUALIFICATIONS
– Experience building machine learning models or developing algorithms for business application
– Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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Manager, Applied Science, Selection Monitoring employer: Amazon
Contact Detail:
Amazon Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Manager, Applied Science, Selection Monitoring
✨Tip Number 1
Familiarise yourself with the latest machine learning technologies and frameworks, especially those mentioned in the job description like MapReduce and Spark. Being able to discuss these tools confidently during your interactions will show that you're not only knowledgeable but also genuinely interested in the role.
✨Tip Number 2
Network with current or former employees of Amazon, particularly those in the Selection Monitoring team or similar roles. They can provide valuable insights into the company culture and expectations, which can help you tailor your approach when discussing your fit for the position.
✨Tip Number 3
Prepare to showcase your problem-solving skills by thinking of examples where you've tackled ambiguous problems in data processing or machine learning. Be ready to discuss your thought process and the impact of your solutions, as this is crucial for a managerial role.
✨Tip Number 4
Stay updated on the latest trends in AI and machine learning, particularly in relation to e-commerce. Being able to discuss how these trends could apply to Amazon's selection and catalog systems will demonstrate your forward-thinking mindset and alignment with the company's goals.
We think you need these skills to ace Manager, Applied Science, Selection Monitoring
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, data processing, and management. Use specific examples that demonstrate your ability to tackle ambiguous problems and lead teams.
Craft a Compelling Cover Letter: In your cover letter, express your passion for applied science and how your background aligns with the role. Mention your experience with technologies like MapReduce, Spark, and AWS, and how you can contribute to Amazon's mission.
Showcase Technical Skills: Clearly outline your technical skills related to machine learning, natural language processing, and analytics. Provide examples of projects where you've successfully built models or algorithms that had a tangible impact.
Highlight Leadership Experience: Since the role requires management experience, emphasise your leadership skills. Discuss how you've managed teams, driven innovation, and delivered complex software systems in previous roles.
How to prepare for a job interview at Amazon
✨Showcase Your Technical Expertise
Make sure to highlight your experience with machine learning, natural language processing, and data analytics. Be prepared to discuss specific projects where you've applied these technologies, especially in a managerial capacity.
✨Demonstrate Problem-Solving Skills
The role involves tackling ambiguous problems, so be ready to share examples of how you've approached complex challenges in the past. Use the STAR method (Situation, Task, Action, Result) to structure your responses.
✨Familiarise Yourself with AWS Technologies
Since the position involves using AWS technologies, it’s beneficial to have a good understanding of the AWS ecosystem. Brush up on services like S3, EC2, and Lambda, and be ready to discuss how you’ve used them in previous roles.
✨Prepare for Behavioural Questions
Expect questions that assess your leadership style and how you manage teams. Think about your approach to mentoring and developing talent, as well as how you handle conflicts or setbacks within a team.
