Principal Applied Scientist | Microsoft Careers

Microsoft

Hybrid

Quick summary

Work type: Hybrid
Location: Redmond, WA
Salary: $142,800–$274,800 / yr
Posted: 8 days ago
Closes: Nov 22, 2026
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $196k

This role $209k

$127k most similar roles pay here $291k

This role pays more than 69% of similar roles. Most pay $177,250–$214,500 — the shaded band above. At the midpoint, this role pays about $209k versus about $196k for comparable roles.

Based on 240 similar postings.

Employer

About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 571 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 522 roles with salary data.

Most-posted roles

View all roles at Microsoft

At a glance

TL;DR · Principal Applied Scientist | Microsoft Careers

Apply Now Log in to save

As a Principal Applied Scientist on the Signals Modeling team, you will lead the development of advanced data-driven attribution and causal measurement methodologies that power our advertising marketplace. Your day-to-day involves defining technical strategies for large-scale learning systems, establishing robust methodologies for incrementality estimation and delayed-feedback modeling, and driving the adoption of these frameworks across bidding, ranking, and optimization processes at web scale. You will work with cutting-edge technologies such as representation learning, weak-supervision techniques, and multi-objective training to build models that remain reliable under noisy data conditions. Essential skills include deep expertise in causal inference, experience leading high-impact initiatives, and the ability to influence technical direction across teams. This role requires a Master's degree or equivalent experience, with a focus on delivering measurable business impact through rigorous scientific methodologies in complex, real-world environments.

Skills

Python Scala R TensorFlow PyTorch Kafka Hadoop Spark PostgreSQL AWS Azure CI/CD Docker Kubernetes Prometheus Grafana Git Jupyter SQL

What you'll do

Define and drive the scientific and technical strategy for data-driven attribution and causal measurement in advertising systems.
Establish methodologies for incrementality estimation, counterfactual learning, delayed-feedback modeling, and bias correction in partially observable environments.
Lead design and production adoption of frameworks improving bidding, ranking, optimization, and advertiser ROI at web scale.
Set evaluation standards distinguishing correlation from causation to elevate experimental rigor across teams.
Identify capability gaps and introduce advanced research or tools to strengthen measurement foundations.
Serve as a subject-matter expert and technical advisor on attribution and causal inference methodologies.

What we're looking for

Master's degree in a relevant field (Statistics, Computer Science, etc.) with 4+ years of related experience.
Proven track record of setting technical direction for large-scale machine learning systems delivering business impact.
Deep expertise in causal inference and data-driven attribution applied in production environments.
Experience leading high-impact initiatives with limited ground truth and critical methodological rigor.
Ability to influence strategy and drive adoption of new measurement approaches across the organization.
Significant experience developing and deploying production ML systems through multiple stages of product lifecycle.
Exceptional communication skills for translating complex technical concepts to senior leaders.