At a Glance
- Tasks: Join a diverse team to solve complex supply chain challenges using data science.
- Company: Amazon Web Services is the leading cloud platform, innovating continuously for global customers.
- Benefits: Enjoy work-life balance, flexible working culture, and opportunities for mentorship and career growth.
- Why this job: Make a real impact in cloud computing while collaborating with talented professionals in an inclusive environment.
- Qualifications: 5+ years of data science experience, strong skills in SQL, Python, and machine learning techniques.
- Other info: Diverse experiences are valued; apply even if you don't meet all qualifications.
The predicted salary is between 48000 - 72000 £ per year.
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.
You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
Do you love problem solving? Are you looking for real world Supply Chain challenges? Do you have a desire to make a major contribution to the future, in the rapid growth environment of Cloud Computing?
Amazon Web Services is looking for a highly motivated Data Scientist to help build scalable, predictive and prescriptive business analytics solutions that supports AWS Supply Chain and Procurement organization. You will be part of the Supply Chain Analytics team working with Global Stakeholders, Data Engineers, Business Intelligence Engineers and Business Analysts to achieve our goals.
We are seeking an innovative and technically strong data scientist with a background in optimization, machine learning, and statistical modeling/analysis. This role requires a team member to have strong quantitative modeling skills and the ability to apply optimization/statistical/machine learning methods to complex decision-making problems, with data coming from various data sources. The candidate should have strong communication skills, be able to work closely with stakeholders and translate data-driven findings into actionable insights. The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment.
Key job responsibilities
- Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard time Series Forecasting techniques like ARIMA, ARIMAX, Holt Winter and formulate ensemble model.
- Proficiency in both Supervised (Linear/Logistic Regression) and Unsupervised algorithms (k means clustering, Principal Component Analysis, Market Basket analysis).
- Experience in solving optimization problems like inventory and network optimization. Should have hands on experience in Linear Programming.
- Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area.
- Detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion.
- Excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions.
- Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers.
About the team
Diverse Experiences: Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
BASIC QUALIFICATIONS
– 5+ years of data scientist experience
– 4+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
– 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
– Experience applying theoretical models in an applied environment
PREFERRED QUALIFICATIONS
– Experience in Python, Perl, or another scripting language
– Experience in a ML or data scientist role with a large technology company
– Functional knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker, Lambda, EC2, Batch, Step Function.
– Experience in creating powerful data driven visualizations to describe your ML modeling results to stakeholders.
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 https://amazon.jobs/content/en/how-we-hire/accommodations 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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Data Scientist II employer: Amazon
Contact Detail:
Amazon Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist II
✨Tip Number 1
Familiarise yourself with AWS services and tools mentioned in the job description, such as S3, Glue, and SageMaker. Understanding these platforms will not only help you during the interview but also demonstrate your genuine interest in the role.
✨Tip Number 2
Brush up on your machine learning and statistical modelling skills, particularly in time series forecasting techniques like ARIMA and ensemble models. Being able to discuss these concepts confidently can set you apart from other candidates.
✨Tip Number 3
Prepare to showcase your problem-solving abilities by thinking of real-world examples where you've applied data science to tackle complex issues. This will help you illustrate your experience and thought process during discussions with the interviewers.
✨Tip Number 4
Network with current or former employees of AWS, especially those in similar roles. They can provide valuable insights into the company culture and expectations, which can be beneficial for your interview preparation.
We think you need these skills to ace Data Scientist II
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly focusing on machine learning, statistical modelling, and optimisation. Use keywords from the job description to demonstrate that you meet the qualifications.
Craft a Compelling Cover Letter: In your cover letter, express your passion for problem-solving and cloud computing. Mention specific projects or experiences that align with the responsibilities outlined in the job description, showcasing your ability to work with diverse teams.
Showcase Technical Skills: Clearly list your technical skills, especially in data querying languages like SQL and scripting languages such as Python. Provide examples of how you've applied these skills in previous roles, particularly in relation to AWS platforms if applicable.
Prepare for Potential Questions: Anticipate questions related to your experience with data analysis tools and techniques. Be ready to discuss specific projects where you used machine learning algorithms or solved optimisation problems, as this will demonstrate your practical knowledge.
How to prepare for a job interview at Amazon
✨Showcase Your Technical Skills
Be prepared to discuss your experience with feature engineering, time series forecasting techniques, and machine learning algorithms. Bring examples of past projects where you applied these skills, as this will demonstrate your technical proficiency.
✨Communicate Clearly with Stakeholders
Since the role involves working closely with various teams, practice explaining complex data-driven insights in simple terms. This will show that you can bridge the gap between technical and non-technical stakeholders effectively.
✨Demonstrate Problem-Solving Abilities
Prepare to discuss specific challenges you've faced in previous roles and how you approached solving them. Highlight your analytical thinking and ability to work through ambiguity, which are crucial for this position.
✨Familiarise Yourself with AWS Tools
Research and understand the AWS platforms mentioned in the job description, such as S3, Glue, and SageMaker. Being knowledgeable about these tools will not only impress your interviewers but also show your commitment to the role.