Principal Applied Scientist, Advertiser Demand Intelligence

Microsoft

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Redmond, WA
Salary
$142,800–$274,800 / yr
Posted
46 days ago
Freshness
Confirmed live yesterday
Closes
Jan 23, 2027

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $237k
This role $209k
$125k most similar roles pay here $307k

This role pays less than 65% of similar roles. Most pay $198,712–$274,621 — the shaded band above. At the midpoint, this role pays about $209k versus about $237k 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 598 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 586 roles with salary data.

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At a glance

TL;DR · Principal Applied Scientist, Advertiser Demand Intelligence

As a Principal Applied Scientist, Advertiser Demand Intelligence, you will define the modeling strategy for an advertising recommendations platform by integrating classical machine learning with generative AI. You will architect end-to-end pipelines for data processing, feature stores, and model training to provide daily insights while leading the development of LLM-based components for intelligent narrative generation. Your role involves building prompt frameworks, fine-tuning strategies, and retrieval-augmented techniques to enable conversational responses to complex sales questions. You will manage technical design reviews, mentor team members, and ensure Responsible AI compliance regarding bias and transparency. Required expertise includes Python, PyTorch or TensorFlow, Azure cloud technologies, and MLOps tools like MLflow. You will apply these skills to solve problems in predictive modeling, anomaly detection, clustering, and time-series forecasting within a complex advertising data environment.

What does a Applied Scientist earn?

Median $208800 from 47 postings across 10 companies.

See salary data

What you'll do

  • Define the modeling strategy for advertising recommendations using both classical machine learning and generative AI.
  • Architect end-to-end machine learning pipelines including data processing, feature stores, training routines, and deployment mechanisms.
  • Lead the integration of LLM components for narrative generation, including prompt engineering and fine-tuning strategies.
  • Mentor and provide technical guidance to the applied science team of scientists and engineers.
  • Establish metrics for success and implement robust monitoring, retraining, and Responsible AI compliance protocols.
  • Translate high-level business objectives into technical plans and communicate complex AI concepts to non-technical stakeholders.
  • Research and experiment with emerging AI trends to keep the platform technologically advanced.

What we're looking for

  • Bachelor's degree with 6+ years experience, Master's with 4+ years, or Doctorate with 3+ years in a relevant quantitative field.
  • 5+ years of experience developing and deploying machine learning solutions in production with end-to-end project ownership.
  • 3+ years of technical leadership experience in an applied science or data science team setting.
  • Extensive hands-on expertise in ML techniques for predictive analytics, pattern recognition, and optimization.
  • Proficiency in programming languages like Python, machine learning frameworks like PyTorch or TensorFlow, and data infrastructure.
  • Deep understanding of NLP and LLMs, including fine-tuning strategies, prompt frameworks, and retrieval-augmented generation.
  • Experience with big data and cloud technologies, specifically Azure or similar platforms for MLOps and large-scale data processing.
  • Proven track record in MLOps, AI governance, and ensuring compliance with Responsible AI standards.

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