below marketmost similar roles pay hereabove market
This role pays more than
54%
of similar roles. Most pay
$146,475–$214,000
— the blue band above.
At the midpoint, this role pays about
$177k
versus about
$180k
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
694 open roles
on FindRole.
Listed pay typically runs
$119,800–$234,700
across 651 roles with salary data.
The Senior Data & Applied Scientist joins the AI for CELA team to transform how legal, regulatory, and public policy professionals manage knowledge and navigate complex environments. You will identify ambiguous problems and build AI-enabled knowledge-management capabilities that convert fragmented communications into structured, reusable institutional knowledge. Day-to-day responsibilities include improving intake triage, enabling high-quality search and summarization, and developing solutions for continuous regulatory intelligence, such as detecting changes and mapping them to obligations. You will utilize statistical analysis, machine learning, and generative AI, specifically focusing on natural language processing, large language models, and agentic workflows. The role requires proficiency in SQL and Python or R to manage structured and unstructured data while ensuring responsible, secure, and auditable AI outcomes within a legal and regulatory context.
Translate ambiguous legal and regulatory problems into clear project plans, measurable success criteria, and technical roadmaps.
Acquire and prepare structured and unstructured data while identifying risks related to privacy, security, bias, and ethics.
Design and evaluate machine learning and generative AI models for classification, retrieval, summarization, and regulatory monitoring.
Write production-quality code to prototype and operationalize scalable AI solutions in partnership with engineering teams.
Define evaluation metrics and human-in-the-loop workflows to connect technical performance to business value and traceability.
Build AI-enabled knowledge-management tools to convert fragmented communications into structured, reusable institutional knowledge.
Develop automated systems for detecting regulatory changes and mapping them to specific obligations and products.
What we're looking for
Hold a Doctorate and 1+ years of data science experience, a Master's and 3+ years, or a Bachelor's and 5+ years of experience.
Hold a Doctorate and 3+ years of data science experience, a Master's and 6+ years, or a Bachelor's and 8+ years of experience (preferred).
Possess advanced knowledge of statistical analysis, experimentation, algorithms, machine learning, and AI (preferred).
Experience managing, transforming, and analyzing structured and unstructured data using SQL and Python, R, or other relevant languages (preferred).
Experience developing, evaluating, or operationalizing scalable machine learning or AI systems including NLP, LLMs, and agentic workflows (preferred).
Demonstrated ability to own complex projects, make decisions amid ambiguity, and collaborate across legal, policy, research, and engineering disciplines (preferred).
Ability to write efficient, readable, and production-quality analysis and software code.
Ability to design and evaluate statistical, machine learning, and generative AI approaches for classification, retrieval, and summarization.
Python
SQL
Machine Learning
Generative AI
Large Language Models
LLMs
Statistical Analysis
Predictive Modeling
Causal Inference
AI Agents
Data Science
Experimentation
Model Evaluation
Production Monitoring
Recommendation Systems
Segmentation
Forecasting
Python
PyTorch
Generative AI
Diffusion Models
VLM
Distributed Training
Multi-modality
Deep Learning
Data Curation
Captioning Pipelines
Image-to-Image
Mid-training
Pre-training
Post-training
Deep Learning
Large Language Models
Python
PyTorch
TensorFlow
C++
C#
Java
C
NLP
Distributed Training
Machine Learning
Predictive Analytics
Search
Document Understanding
High Throughput Systems