Description

Amazon's Customer Service (CS) department is seeking a senior Data Scientist to lead the scientific direction of the Data Analytics Support Hub (DASH) Advanced Analytics team. CS is the heart of Amazon; our vision is to be Earth's most customer-centric company. The successful candidate will be the scientific leader within the Advanced Analytics branch, setting the methodological bar and driving Q&E's most complex diagnostic and predictive analytics across a worldwide, cross-vertical scope.

As a Data Scientist III, you will define the scientific strategy for Q&E's transition from descriptive to diagnostic and predictive analytics. You will own the measurement frameworks for pioneering KPIs where no prior art exists, lead the multi-contact journey science (Transfers, Repeats, DART, ECR/VPI), and be the scientific voice in partnership with central teams. You will be hands-on on 2-3 flagship programs while being accountable for the scientific bar across the entire branch.


Key job responsibilities

Responsibilities include but are not limited to:

- Set the scientific direction for the Advanced Analytics branch across flagship initiatives.
- Define measurement frameworks for Q&E-pioneering KPIs where no prior art exists (QoS, FIR, Outlier Behavior).
- Own the scientific framework for multi-contact journey analysis: threading interactions, attributing root cause across touchpoints, separating preventable vs. necessary events.
- Choose the right methods (statistical, causal, ML, LLM, hybrid) for each problem and justify trade-offs. Drive excellence in evaluation: ground-truth construction with Quality auditors, human audits, precision/recall, drift, calibration, bias, safety, and cost.
- Design driver-analysis and bridging methods that explain KPI movement (WoW, MoM, YoY, vs OP2) across dimensions for WBR "why" automation consumed by senior leadership.
- Represent DASH in Senior Manager / Director reviews, CS-LT forums, and partner-team design reviews. Build consensus on contentious scientific and architectural decisions.
- Partner with Data Engineers on productionization, Shepherd risk, App Security red-certification, Kale, Legal, Threat Models, for scientific assets.
- Mentor team members; provide promotion assessments; contribute to hiring at DS II and DS III. Represent Q&E in the broader Amazon Data Science community.
- Produce design docs, technical documentation, and review artifacts.