Amazon.com Services LLC

Technology

DataScientistII

$136–184k Seattle, Washington, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Data Scientist II at Amazon.com Services LLC. Skills: Machine learning, Data science, Analytics. Understand causal inference models. Assess marketing campaigns”

Industry & Context.

Technology
Problems you'll solve

Address business questions; Solve problems

What They're Looking For.

Must Have

2+ years of data scientist experience, 3+ years of data querying languages experience, 3+ years of scripting languages experience, 3+ years of statistical/mathematical software experience, 3+ years of machine learning/statistical modeling experience, 3+ years of data analysis tools and techniques experience

Nice to Have

PhD preferred, Specific ML framework experience, Cloud platform certs

What You'll Do.

Understand causal inference models

Assess marketing campaigns

Assess online experiments

Assess uplift analysis

Understand business reality

Develop meaningful solutions

Work with business teams

Work with engineering teams

Work with partner teams

Innovate modeling techniques

Adapt modeling procedures

Perform exploratory data analysis

Fine tune Amazon LLMs

Handle large blocks of text

Solve summarization tasks

Prevent catastrophic forgetting

Work with huge datasets

Bring datasets together

Answer business questions

Implement data flow solutions

Operate data flow solutions

Create fault tolerant solutions

Create self-healing solutions

Create adaptive solutions

How You'll Work.

Team & Collaboration

Internal stakeholders; Cross-functional teams; Business teams; Engineering teams; Partner teams

Process & Methodology

Analytics roadmap

Full Job Description

How to use the world’s richest collection of e-commerce data to improve payments experience for our customers? Amazon Payments Data Science team seeks a Data Scientist for building analytical solutions that will address increasingly complex business questions in the Amazon Currency convertor space. Amazon.com has a culture of data-driven decision-making and demands insights that are timely, accurate, and actionable. This team provides a fast-paced environment where every day brings new challenges and new opportunities. As a Data Scientist in this team, you will be driving the analytics roadmap and will provide descriptive and predictive solutions to the Amazon currency convertor business team through a combination of Gen AI, LLM and other machine learning techniques for text analytics, segmentation and prediction. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. Key job responsibilities • Understand the applications of causal inference models on real datasets, including assessment of marketing campaigns, online experiments, uplift analysis etc • Understand the business reality behind large sets of data and develop meaningful solutions comprising of analytics as well as marketing management • Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus are • Innovate by adapting new modeling techniques and procedures • Effective exploratory data analysis, and model building using industry standard regression and classification techniques such as Random Forest, XGBoost package, Keras framework • Demonstrate thorough technical knowledge Fine Tuning of Amazon LLMs to handle large blocks of text, using Generative AI to solve for summarization tasks and prevent catastrophic forgetting, feature engineering of massive datasets, • Be pass

Free ATS check

Applying for this Data Scientist II role?

Most applicants get filtered before a human reads their resume. See if yours makes the cut.

ANONYMOUS · UNFILTERED

What do employees actually say about Amazon.com Services LLC?

Real rants from real employees. Read before you apply.

Read Company Rants →