Data Scientist II, Payment Risk Machine Learning

Amazon; London; On-site; GBP 50,000 - 80,000; Full time

Job summary

A leading global e-commerce company is seeking a data scientist for its Risk Mining Analytics team in London. The role involves analyzing large datasets, building statistical models, and collaborating with cross-functional teams to improve operational efficiency and security. Candidates should have a strong background in data science, including proficiency in SQL, Python, and machine learning techniques.

Qualifications

• 2+ years of experience as a data scientist.
• 3+ years using SQL and Python.
• Experience in machine learning techniques.

Responsibilities

• Analyze terabytes of data to deliver complex insights.
• Build machine learning models for transaction legitimacy.
• Collaborate with cross-functional teams to enhance automation.

Skills

SQL

Python

Machine Learning

Statistical Analysis

Education

Experience in applied data science

Tools

R

SAS

Matlab

Job description

Amazon.com’s Buyer Risk Prevention (BRP) mission is to make Amazon the safest and most trusted place worldwide to transact online. Amazon runs one of the most dynamic e-commerce marketplaces in the world, with nearly 2 million sellers worldwide selling hundreds of millions of items in ten countries. BRP safeguards every financial transaction across all Amazon sites. As such, BRP designs and builds the software systems, risk models, and operational processes that minimize risk and maximize trust in Amazon.com.

The BRP organization is looking for a data scientist for its Risk Mining Analytics (RMA) team, whose mission is to combine advanced analytics with investigator insight to detect negative customer experiences, improve system effectiveness, and prevent bad debt across Amazon.

As a data scientist in risk mining, you will be responsible for modeling complex problems, discovering insights, and building risk algorithms that identify opportunities through statistical models, machine learning, and visualization techniques to improve operational efficiency and reduce bad debt.
You will need to collaborate effectively with business and product leaders within BRP and cross-functional teams to build scalable solutions against high organizational standards. The candidate should be able to apply a breadth of tools, data sources, and data science techniques to answer a wide range of high-impact business questions and proactively present new insights in a concise and effective manner.

The candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high-impact role with goals that directly impact the bottom line of the business.

Key job responsibilities
Analyze terabytes of data to define and deliver on complex analytical deep dives to unlock insights and build scalable solutions through Data Science to ensure security of Amazon’s platform and transactions

Build Machine Learning and/or statistical models that evaluate the transaction legitimacy and track impact over time

Ensure data quality throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, and cross-lingual alignment/mapping

Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams

Develop efficient data querying infrastructure for both offline and online use cases

Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes

Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use.

Maintain technical document and communicate results to diverse audiences with effective writing, visualizations, and presentations

BASIC QUALIFICATIONS

- 2+ years of data scientist experience
- 3+ 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 a ML or data scientist role with a large technology company

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