Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Data Scientist II

Amazon
London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Scientist II, Analytics - Landing

Data Scientist II (TBH5177)

Data Scientist III, Planning and Insights

Data Scientist II, PLS Analytics

Data Scientist III, Planning and Insights

Product Data Scientist II (Based in Dubai, UAE)

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

  1. 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.
  2. Proficiency in both Supervised (Linear/Logistic Regression) and Unsupervised algorithms (k means clustering, Principal Component Analysis, Market Basket analysis).
  3. Experience in solving optimization problems like inventory and network optimization. Should have hands on experience in Linear Programming.
  4. Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area.
  5. 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.
  6. 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.
  7. 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.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.

Why Now Is the Perfect Time to Launch Your Career in Machine Learning: The UK's Intelligence Revolution

The United Kingdom stands at the epicentre of a machine learning revolution that's fundamentally transforming how we solve problems, deliver services, and unlock insights from data at unprecedented scale. From the AI-powered diagnostic systems revolutionising healthcare in Manchester to the algorithmic trading platforms driving London's financial markets, Britain's embrace of intelligent systems has created an extraordinary demand for skilled machine learning professionals that dramatically exceeds the current talent supply. If you've been seeking a career at the forefront of technological innovation or looking to position yourself in one of the most impactful sectors of the digital economy, machine learning represents an exceptional opportunity. The convergence of abundant data availability, computational power accessibility, advanced algorithmic development, and enterprise AI adoption has created perfect conditions for machine learning career success.

Automate Your Machine Learning Jobs Search: Using ChatGPT, RSS & Alerts to Save Hours Each Week

ML jobs are everywhere—product companies, labs, consultancies, fintech, healthtech, robotics—often hidden in ATS portals or duplicated across boards. The fastest way to stay on top of them isn’t more scrolling; it’s automation. With keyword-rich alerts, RSS feeds, and a reusable ChatGPT workflow, you can bring relevant roles to you, triage them in minutes, and tailor strong applications without burning your evenings. This is a copy-paste playbook for www.machinelearningjobs.co.uk readers. It’s UK-centric, practical, and designed to save you hours each week. What You’ll Have Working In 30 Minutes A role & keyword map spanning LLM/NLP, Vision, Core ML, Recommenders, MLOps/Platform, Research/Applied Science, and Edge/Inference optimisation. Shareable Boolean searches you can paste into Google & job boards to cut noise. Always-on alerts & RSS feeds delivering fresh roles to your inbox/reader. A ChatGPT “ML Job Scout” prompt that deduplicates, scores fit, and outputs tailored actions. A lightweight pipeline tracker so deadlines and follow-ups never slip.