This role pays more than
60%
of similar roles. Most pay
$142,275–$208,668
— the shaded band above.
At the midpoint, this role pays about
$177k
versus about
$175k
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.
As a Senior Data and Applied Scientist within the Commercial Business & AI team, you will join an agile group focused on developing model evaluation frameworks, optimization pipelines, and experimentation platforms. You will partner with engineering and product management teams to solve complex business challenges for Dynamics 365 applications used in sales, marketing, and support. Your daily responsibilities include translating business needs into measurable objectives, writing robust code for analysis, and developing new machine learning or GenAI models using advanced statistical techniques. You will also lead the evaluation of GenAI solutions to identify root causes for fine-tuning or reinforcement learning fixes. The role requires proficiency in Python, R, SQL, KQL, PySpark, and modern analytics frameworks, alongside experience with large-scale enterprise data platforms like Fabric, Synapse, Databricks, and Azure Machine Learning tools.
Translate business needs into manageable problems with well-defined measurable objectives and outcomes.
Create implementation plans by defining success metrics and selecting appropriate algorithms and tools.
Write robust, reusable, and extensible code to support data analysis and modeling.
Develop new machine learning or Generative AI models using advanced statistical techniques.
Evaluate GenAI solutions to diagnose issues and identify root causes for fine-tuning or reinforcement learning.
Utilize AI-powered tools to accelerate coding, analysis, and daily technical tasks.
What we're looking for
A PhD in a relevant field and 1+ years of data science experience, or a Master's degree and 3+ years of experience, or a Bachelor's degree and 5+ years.
Equivalent professional experience to the specified educational and experience requirements is acceptable.
Experience in Python, R, SQL, KQL, PySpark, and modern analytics frameworks (preferred).
Machine Learning
Generative AI
Natural Language Processing
Large Language Models
Python
SQL
R
Data Science
Retrieval
Agentic Workflows
Statistical Analysis
Metadata Extraction
knowledge-management
Machine Learning
Deep Learning
Large Language Models
Python
C++
C#
Java
PyTorch
TensorFlow
NLP
Distributed Training
Search
Statistics
Predictive Analytics
C