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Amazon
Amazon

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Applied Scientist II, Amazon Business, Amazon Business - GTMO Science

職種機械学習
経験ミドル級
勤務地Madrid, M, ESP
勤務オンサイト
雇用正社員
掲載2週間前
応募する

Come be a part of a rapidly expanding $35 billion-dollar global business. At Amazon Business, a fast-growing startup passionate about building solutions, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech & retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations thrive. At Amazon Business, we strive to be the most recognized and preferred strategic partner for smart business buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes and industries. Unlock your career potential.

The AB Go-To-Market Operations Science team (GTMO - Science) is revolutionizing sales productivity through AI-powered solutions. We develop transformative tools that help Account Executives (AEs) to prioritize accounts, recommend product features, and engage more effectively with customers. We partner closely with Product, tech, BI, sales, and marketing teams to launch and scale high-impact global AI products. We're seeking an Applied Scientist to join our team to improve the productivity and efficiency of AEs. You'll be part of expanding GenAI capabilities and scaling its impact across global markets.

A successful Applied Scientist at Amazon demonstrates bias for action and operates in a startup environment, with leadership skills, and proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. We need great leaders to think big and design new solutions to solve complex problems using machine learning (ML) and Generative AI techniques to improve our customers’ experience when using AB. You have hands-on experience making the right decisions about technology, models and methodology choices.

Key job responsibilities
As an Applied Scientist, you will primarily leverage machine learning techniques and generative AI to outreach customers based on their life cycle stage, behavioral patterns, and purchase history. You may also perform text mining and insight analysis of real-time customer conversations and make the model learn and recommend the solutions. Your work will directly impact the trust customers place in Amazon Business. You will partner with product management and technical leadership to identify opportunities to innovate customer journey experiences.
Additional responsibilities include:

  • 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
  • Design and lead large projects and experiments from beginning to end, and drive solutions to complex or ambiguous problems
  • Use broad expertise to recommend the right strategies, methodologies, and solve challenges using statistical modeling, machine learning, optimization, and/or other approaches for quantifiable impact on the business
  • Build models that measure incremental value, predict growth, define and conduct experiments to optimize engagement of AB customers, and communicate insights and recommendations to product, sales, and finance partners.

A day in the life
In this role, you will be a technical expert with significant scope and impact. You will work with Technical Product Managers, Data Engineers, other Scientists, and Salesforce developers, to build new and enhance existing ML models to optimize customer experience. You will prototype and test new ideas, iterate quickly, and deploy models to production. Also, you will conduct in-depth data analysis and feature engineering to build robust ML models.

Basic Qualifications

  • PhD, or a Master's degree and experience in CS, CE, ML or related field
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience with programming in Python language
  • Experience in solving business problems through machine learning, data mining, Reinforcement learning and statistical algorithms

Preferred Qualifications

  • Technical fluency; comfort understanding and discussing architectural concepts and algorithms, schedule tradeoffs and new opportunities with technical team members.
  • Excellent critical thinking skills, combined with the ability to present your beliefs clearly and compellingly in both verbal and written form.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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.

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Amazonについて

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

従業員数

Seattle

本社所在地

$1.5T

企業価値

レビュー

10件のレビュー

3.4

10件のレビュー

ワークライフバランス

2.5

報酬

4.2

企業文化

3.0

キャリア

3.8

経営陣

2.7

65%

知人への推奨率

良い点

Great benefits and competitive pay

Learning and advancement opportunities

Good teamwork and colleagues

改善点

High pressure and long hours

Poor work-life balance

Toxic work culture and management issues

給与レンジ

4件のデータ

Junior/L3

L2

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

L3

L4

L5

Junior/L3 · Data Scientist L4

0件のレポート

$181,968

年収総額

基本給

-

ストック

-

ボーナス

-

$154,672

$209,264

面接レビュー

レビュー6件

難易度

4.0

/ 5

期間

21-35週間

体験

ポジティブ 0%

普通 17%

ネガティブ 83%

面接プロセス

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Technical Interview

6

Onsite/Virtual Interviews

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge