Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Sr. Data Scientist, FCGT

Amazon
London
3 months ago
Applications closed

Related Jobs

View all jobs

Sr. Data Scientist, GenAI Algorithms (Based in Dubai)

Sr Data Scientist (London)

Sr Data Scientist (London)

Sr Data Analyst

Associate Director, AI Data Scientist

Sr. Data Engineer - Lenovo AI Technology Center

Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. Amazon's evolution is driven by the spirit of innovation that is part of the company's DNA.


Amazon Seller Services is looking for a Data Scientist to work hands on from concept to delivery on generative AI, statistical analysis, prescriptive and predictive analysis, and machine learning implementation projects. We are looking for a problem solver with strong analytical skills and a solid understanding of statistics & Machine learning algorithms as well as a practical understanding of collecting, assembling, cleaning and setting up disparate data from enterprise systems.


Key Job Responsibilities

  1. Ability to understand a business problem and the available data and identify what statistical or ML techniques can be applied to answer a business question.
  2. Given a business problem, estimate solution feasibility and potential approaches based on available data.
  3. Understand what data is available, where, and how to pull it together. Work with partner teams where needed to facilitate permissions and acquisition of required data.
  4. Quickly prototype solutions and build models to test feasibility of solution approach.
  5. Build statistical models/ ML models, train and test them to drive towards the optimal level of model performance.
  6. Improve existing processes with development and implementation of state of the art generative AI models.
  7. Work with technology teams to integrate models by wrapping them as services that plug into Amazon's marketplace and fulfillment systems.
  8. Work across the spectrum of reporting and data visualization, statistical modeling and supervised learning tools and techniques and apply the right level of solution to the right problem.
  9. The problem set covers aspects of detecting fraud and abuse, improving performance, driving lift and adoption, recommending the right upsell to the right audience, cost saving, selection economics and several others.

BASIC QUALIFICATIONS

  • 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience.
  • 5+ years of data scientist experience.
  • Experience with statistical models e.g. multinomial logistic regression.

PREFERRED QUALIFICATIONS

  • Experience working with data engineers and business intelligence engineers collaboratively.
  • Experience managing data pipelines.
  • Experience as a leader and mentor on a data science team.

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 visitthis linkfor more information.

Posted:January 15, 2025

Posted:November 25, 2024

Posted:December 12, 2024

Posted:January 10, 2025

Posted:January 9, 2025

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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.

Jobs

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Jobs

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Jobs

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.