Senior Data Scientist

Quick Facts

• Role: Senior Data Scientist

• Focus: End-to-end yield optimization for Azure infrastructure (virtual machines, storage)

Description

Lead yield optimization initiatives by framing ambiguous business problems and translating revenue, hardware, and capacity data into actionable insights. Use analytics, machine learning, causal inference, and visualization to recommend pricing and resource-allocation strategies, influence cross-functional decisions, and measure business outcomes.

Responsibilities

• Write efficient, readable code in Python, SQL, KQL (or similar) to prepare and analyze large-scale revenue and capacity datasets using distributed data processing.

• Select, develop, and validate statistical and machine-learning approaches for resource allocation and pricing; assess limitations and significance.

• Partner with business planning, engineering, product management, and finance to define objectives, prioritize work, and align yield strategies with business goals.

• Design experiments and measure impact for optimization hypotheses using success metrics, guardrails, and result interpretation.

• Build causal inference models (e.g., difference-in-differences, synthetic control) when randomized experiments aren’t feasible; estimate demand elasticity and substitution effects.

• Create decision-relevant metrics, dashboards, and narratives; present trade-offs and analytical limitations to technical and executive audiences.

• Stay current on AI, cloud economics, and optimization techniques; mentor through code reviews and best practices.

• Apply understanding of Azure pricing, cloud economics, and customer workflows to shape recommendations and explain business trade-offs.

Benefits

Benefits and additional compensation may be available; see the company pay and benefits information page.

Requirements

• Doctorate with 1+ year data-science experience, or Master’s with 3+ years, or Bachelor’s with 5+ years, or equivalent experience.

• Experience managing structured and unstructured data and applying statistical techniques to reporting results.

• Preferred: experience with yield/revenue management, pricing optimization, or cloud resource allocation.