Director - Applied Science, Amazon Connect

Saved job description

The Amazon Connect Interactive AI and Engagement organization was formed in April 2025 to bring together Contact Lens, Q in Connect, and Flows/Lex into one organization, responsible for weaving native-AI across the Connect application experiences delivered to end-customers, agents, and managers/supervisors. We are reimagining customer engagement to enable companies to deliver proactive and personalized experiences (in websites, mobile apps, and traditional contact center channels including voice, messaging, and email) that discern and resolve end-customers' intent before problems ever arise. To succeed, we need a unified science strategy and approach to power 'AI-throughout' customer experiences that leverage humans in the loop when required to meet business goals. We seek to hire a Director of Applied Science who will define and execute that strategy, and organization required. This leader will push the technical boundaries in generative AI science, shaping the industry, while influencing and leading key product investments across Connect service teams and leadership.

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.

Requirements: 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