热门公司

招聘

职位Amazon

Business Research Analyst - II, RBS

Amazon

Business Research Analyst - II, RBS

Amazon

Bengaluru, KA, IND

·

On-site

·

Full-time

·

2w ago

As a Research Analyst, you'll collaborate with experts to develop and own advance machine learning and AI solutions for business needs. You'll drive product pilots, demonstrating innovative thinking and customer focus. You'll build scalable solutions, write high-quality code, and develop state-of-the-art AI models. You'll coordinate between science and software teams, optimizing solutions. The role requires thriving in ambiguous, fast-paced environments and working independently with AI models.

  • Key job responsibilities
  • Collaborate with Applied Scientists to implement ML/LLM solutions that meet business goals
  • Conduct product pilots demonstrating customer obsession and innovation
  • Develop scalable solutions by writing high-quality code, building ML/LLM models using current research breakthroughs and implementing performance optimization techniques
  • Act as a bridge between science and software teams to deliver optimized solutions
  • Communicate technical concepts to stakeholders at all levels
  • Develop technical documentation for Design specifications, Algorithms, Implementation challenges and Performance metrics
  • Monitor and maintain existing solutions to ensure peak performance

About the team
The Retail Business Systems (RBS) group is an integral part of Amazon online product lifecycle and buying operations. The team is designed to ensure Amazon remains competitive in the online retail space with the best catalog quality, wide selection, supply chain defects and compliance programs. The team’s primary role is to create and enhance retail selection on the worldwide Amazon online catalog. The tasks handled have a direct impact on customer buying decisions and online user experience.

Basic Qualifications

  • Bachelor's degree in sciences, engineering, finance or equivalent
  • 2+ years of software development experience
  • Experience with large distributed IT systems
  • Experience using data and metrics to drive improvements
  • Experience in Strong hands-on programming skills in Python, SQL, Hadoop/Hive. Additional knowledge of Spark, Scala, R, Java desired but not mandatory.
  • 4+ years of machine learning, statistical modeling, data mining, and analytics techniques experience

Preferred Qualifications

  • Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
  • Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
  • Master's degree in sciences, engineering, finance or equivalent
  • Experience designing large-scale systems and applications

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