Principal Data and Applied Scientist
Core
Define scientific strategy to measure AI business impact, develop GenAI models, and lead end-to-end evaluation of AI solutions.
Role type
Principal Data and Applied Scientist (AI Impact & GenAI)
Builds
Causal inference frameworks, GenAI models, and scalable impact measurement pipelines.
Domain
Artificial Intelligence, Generative AI, Causal Inference, Business Analytics
Deliverable
production ML models | dashboards & analysis
Required skills
Causal inference, A/B testing, experimental design, GenAI model development, LLM techniques, statistical analysis, Python, PySpark, SQL, Azure Machine Learning, Azure AI Foundry, Azure OpenAI, Spark cluster optimization, Azure Synapse/Databricks, technical writing, executive communication
Preferred skills
None stated
Technologies
Python, PySpark, SQL, Azure Machine Learning, Azure AI Foundry, Azure OpenAI, Azure Synapse, Databricks
Responsibilities
Translate ambiguous business questions into well-scoped scientific problems with clear hypotheses; Own the scientific and statistical strategy for measuring AI business impact; Define and govern the metric framework connecting AI adoption to downstream outcomes; Develop ML and GenAI models using advanced statistical and LLM techniques; Lead end-to-end evaluation of GenAI solutions including quality diagnosis and fine-tuning recommendations; Write robust, reusable code and analytical pipelines for scalable impact measurement; Communicate findings and tradeoffs to senior leadership to influence investment decisions; Mentor team members and raise the scientific bar through design reviews.
Seniority
Principal, strategy & mentorship
