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Sr. Data Scientist, Alexa Connections

Amazon

Sr. Data Scientist, Alexa Connections

Amazon

Vancouver, BC, CAN

·

On-site

·

Full-time

·

3w ago

As a Sr. Data Scientist in Alexa Connections, you will lead the end-to-end development of machine learning and data science solutions that power intelligent communication experiences across channels such as calling, messaging and email. You will partner closely with product, engineering, and business leaders to translate ambiguous problems into scalable ML models, experimentation frameworks, and data-driven product decisions. In this role, you will design and deploy advanced ML and statistical models for capabilities such as prioritization, intent detection, and proactive action recommendations. You will analyze large-scale datasets and run rigorous experiments, including A/B testing and causal analysis, to measure impact and continuously improve customer engagement and product performance. Additionally, you will shape the applied science roadmap and collaborate with global cross-functional teams to deliver AI-driven solutions that scale to millions of Alexa customers.

  • Key job responsibilities

  • Partner with product, engineering, operations, and security teams to translate complex business problems into scalable, production-ready data science and ML solutions.

  • Own the full lifecycle of model development, including exploratory analysis, model design, deployment, monitoring, and continuous improvement.

  • Define and track success metrics, conduct rigorous analyses, and provide insights that guide product launches, feature improvements, and data-driven decision-making.

  • Build data-driven business cases to prioritize science initiatives and demonstrate measurable impact of ML solutions.

  • Develop ML-powered systems supporting key business areas.

  • Lead research and analysis to understand customer interactions with Alexa, and enhance overall customer experience.

  • Contribute to the broader science community by mentoring analysts, improving data workflows and tooling, and publishing technical work in internal and external forums.

  • A day in the life

  • Deep dive into our business metrics, analyze data, trends, and reviewing dashboards

  • Writing code: building packages in Python, writing SQL queries, deploying solutions for Connections experience teams to consume.

  • Leading or joining working sessions with Product Managers to refine problem statements new initiatives.

  • Exploring new features and model architectures, leveraging AWS services, documentation, and upskilling yourself to the latest technologies.

  • Leverage pre-trained LLMs to build applications that solve business problems for Connections experiences.

  • Meet with Sr. Engineers/Principal Engineers to align on solution designs.

  • Own or co-own MBR, WBR documents that are reviewed with Connections leadership team.

About the team
Alexa Connections aspires to make Alexa+ the world’s most trusted connection assistant for getting things done and creating moments of joy. Our vision emphasizes a) Trust as our foundation for becoming a daily habit, knowing our customers have plentiful choices, b) Completion of end-to-end customer journeys, beyond shipping features, and c) Joy through personalized, proactive experiences, that create a memory.

Basic Qualifications

  • Bachelor's degree
  • 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 4+ years of data scientist experience
  • Experience with statistical models e.g. multinomial logistic regression

Preferred Qualifications

  • 2+ years of data visualization using AWS Quick Sight, Tableau, R Shiny, etc. experience
  • Experience managing data pipelines
  • Experience as a leader and mentor on a data science team

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.

CAN, BC, Vancouver - 143,200.00 - 239,100.00 CAD annually

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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