At a Glance
- Tasks: Design and develop models to optimise inventory and product flows in the supply chain.
- Company: Join Amazon, a leader in e-commerce and innovation.
- Benefits: Competitive salary, diverse work culture, and opportunities for growth.
- Other info: Collaborative environment with a focus on diversity and inclusion.
- Why this job: Make a real impact on global supply chain efficiency and customer satisfaction.
- Qualifications: Experience with data scripting languages and statistical models required.
The predicted salary is between 60000 - 80000 £ per year.
Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you?
Key Responsibilities
- Design and develop mathematical models to optimize inventory placement and product flows.
- Design and develop statistical and optimization models for planning Supply Chain under uncertainty.
- Manage several high-impact projects simultaneously.
- Consult and collaborate with business and technical stakeholders across multiple teams to define new opportunities to optimize our Supply Chain.
- Communicate data-driven insights and recommendations to diverse senior stakeholders through technical and/or business papers.
- Leverage LLMs to improve explainability of our optimization solutions and drive engagement from supply chain planners across the world.
Basic Qualifications
- Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent).
- Experience working as a Data Scientist.
- Experience with statistical models e.g. multinomial logistic regression.
- Experience working with data engineers and business intelligence engineers collaboratively.
Preferred Qualifications
- Experience with data visualization using Tableau, Quicksight, or similar tools.
- Experience managing data pipelines.
- Experience as a leader and mentor on a data science team.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon.
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information.
Data Scientist, network planning optimization world wide, Supply Chain Optimization Technology employer: Amazon Science
At Amazon, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Data Scientist in our Supply Chain Optimization Technology team, you'll have the opportunity to work on high-impact projects that directly influence our global operations, while benefiting from extensive employee growth opportunities and a commitment to diversity and inclusion. Our location provides a vibrant environment where your contributions will be valued, and you can thrive in a role that is both meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist, network planning optimization world wide, Supply Chain Optimization Technology
✨Get Involved in Data Science Meetups
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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Scientist, network planning optimization world wide, Supply Chain Optimization Technology at Amazon Science.
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We think you need these skills to ace Data Scientist, network planning optimization world wide, Supply Chain Optimization Technology
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Amazon Science, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Amazon Science. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Amazon Science
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Amazon Science!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
