热门公司

招聘

职位Amazon

Ml Data associate II, ABDAI

Amazon

Ml Data associate II, ABDAI

Amazon

Hyderabad, TS, IND

·

On-site

·

Full-time

·

6d ago

Over the past 25 years, Amazon has reinvented on behalf of customers and has become the largest internet retailer and marketplace in the world. Amazon is now reinventing on behalf of the business customer and focused on building the most innovative Business-to-Business (B2B) marketplace in the world, and we are recruiting to make this vision a reality.

The Amazon Business organization is focused on building solutions to enable B2B customers to research, discover and buy business, industrial and scientific products in large catalogs; across multiple devices, marketplaces and regions. Our customers have different needs than the traditional Amazon consumer customer base. Amazon Business (AB) reseller team focuses on the investigations with researches on AB customers on various parameters and evaluates facts related to buyer and/or seller to unblock the legit customer to on large quantity purchases.

Key job responsibilities
This role would need you to 1) Handle the day-to-day assigned tasks and ensure they meet quality standards 2) Maintain records of day-to-day work by updating trackers to reflect work done 3) Use tools to create and manage classification 4) Actively troubleshoot and respond to issues that are caused by incorrect classification

About the team
Amazon Business Data Analytics and Insights (ABDAI) has two missions; (1) provide accurate and reliable, data and data products for continued success of our business and (2) predict and value customer actions for our business partners to be right a lot when taking decision

A day in the life
This role requires strong attention to detail, solid work ethic and drive, the ability to manage large and complex rule sets, the ability to recommend solutions to various problems and excellent communication skills and follow up. · Bachelor Degree or equivalent; · Decision making aptitudes based on given guidelines and in ambiguous context. · Self-motivated with critical attention to detail, deadlines and reporting; · Proficiency in Microsoft Excel and Word · Demonstrated collaborative skills and ability to work well within a team, including adherence to core values and dynamic corporate culture · Ability to work under a dynamic work environment and meet performance goals.

Basic Qualifications

  • Experience in natural language data labeling, data annotation, linguistic annotation or other forms of data markup

Preferred Qualifications

  • Bachelor's degree or equivalent

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.

总浏览量

0

申请点击数

0

模拟申请者数

0

收藏

0

关于Amazon

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+

员工数

Seattle

总部位置

$1.5T

企业估值

评价

2.9

10条评价

工作生活平衡

2.8

薪酬

3.7

企业文化

2.5

职业发展

2.3

管理层

2.1

35%

推荐给朋友

优点

Good pay and compensation

Strong benefits package

Flexible scheduling options

缺点

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

薪资范围

4个数据点

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L4

0份报告

$181,968

年薪总额

基本工资

-

股票

-

奖金

-

$154,672

$209,264

面试经验

10次面试

难度

3.7

/ 5

时长

21-35周

录用率

20%

体验

正面 10%

中性 10%

负面 80%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge