AmazonDirector - Applied Science, Amazon Connect
Amazon is hiring a Director - Applied Science, Amazon Connect in Seattle, United States. It pays $289k-$350k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include Bedrock, SQL and Spark.
- Level classifies it as an executive role.
- Level lists 21,000+ other open roles at Amazon.
- The role was posted within the past week.
AI in this role
Lead the applied science strategy and team for Amazon Connect to integrate native generative AI across customer experiences.
The business opportunity is substantial. We are executing to be the leader irrespective of the ultimate balance between proactive end-customer self-service and agent-assisted workloads. To do so, science innovation will be pivotal to help achieve our ambitious goals, differentiating Amazon Connect from our competitors.
Key job responsibilities
The Director of Applied Science will lead us to propose and deliver an organizational plan that is aligned to a unified science strategy. This science strategy will enable data-driven, AI-powered continuous optimization across self-service, agent assistance, and manager assistance workloads. This leader will inherit an existing applied science team, and possibly (strategy dependent) a data integrations team engineers. We believe that the strategy this leader defines will require additional applied scientists. Beyond direct team ownership, this leader will be responsible for cross-AWS science collaboration with Bedrock, AGI, Q, and Transcribe organizations.
Basic qualifications
Basic qualifications
• A MS in CS, Machine Learning, Statistics, Operations Research or similar.
• 10 years of hands-on experience in predictive modeling and large data analysis
• Expertise in Machine Learning as applied to large-scale generative models
• Strong ML breadth and depth
• Strong skills with SQL
• Strong skills with Spark/Python/Perl (or similar)
• Communication and data presentation skill
• Strong problem-solving ability
Preferred qualifications
• A PhD in Computer Science, Machine Learning, Statistics or Operations Research
• 15 years of industry experience in ML
• Superior ML breadth and depth
• Expert skills with SQL
• Expert skills with Spark/Python/Perl (or similar)
• Superior problem solving
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. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, NY, New York - 288,700.00 - 350,000.00 USD annually
USA, WA, Seattle - 262,500.00 - 350,000.00 USD annually
How we rate this
Director - Applied Science, Amazon Connect at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where applied science was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where generative ai was part of your work. What did you do?
- Tell me about a project where predictive modeling was part of your work. What did you do?
- Tell me about a project where team leadership was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Applied Science, Machine learning, Generative AI, Predictive Modeling, and Team Leadership. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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