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.
Basic Qualifications
- Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
- Experience working as a Data Scientist
- Experience with statistical models e.g. multinomial logistic regression
- Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
- PhD in computer science, machine learning, engineering, or related fields, or experience working as a Data Scientist
- Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience working with data engineers/business intelligence engineers collaboratively
- Experience leading applied LLM/GenAI programs end-to-end: prompt design, eval frameworks, RAG/agentic pipelines, safety and hallucination mitigation, cost/latency/scale trade-offs
Preferred Qualifications
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience building data pipelines or automated ETL processes
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering
- Master's degree in econometrics, statistics, industrial engineering, operations research, optimization, data mining, analytics, or equivalent quantitative field, or Master's degree
- Experience in contact-center, conversational AI, or CX domains with multi-touchpoint journey analytics
- Experience navigating Amazon production processes: Shepherd, App Security, ASR, Kale, Legal, Threat Models,
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