AI Value Governance & Insights Lead at Morgan Stanley focusing on building AI value management capabilities. Driving forecasting and optimization of AI costs and collaborating across teams in a hybrid role.
Responsibilities
Define and implement data-driven approaches to align AI spend with measurable business outcomes
Drive AI spend forecasting and financial analytics using advanced analytics and machine learning
Integrate AI usage telemetry data to standardize tokenomics and usage tracking
Design the scalable self-service analytics platforms
Provide local leadership and strategic oversight to a small engineering team
Collaborate with cross-functional stakeholders to gather requirements
Proactively evaluate emerging technologies for innovation, efficiency, and cost optimization
Drive documentation, knowledge sharing, and thought leadership across AI, data engineering, and architecture communities
Requirements
10+ years of experience in data analytics, data engineering, data science, or AI related field
Strong Python expertise for data manipulation and advanced analytics (Pandas, NumPy, SciPy, PySpark)
Proficiency in SQL and experience with large-scale cloud data platforms (e.g., Snowflake, Databricks, Dataiku)
Strong understanding of data architecture, data modelling, and data warehousing concepts
Exposure to AI/LLM tokenomics
Hands-on experience with data pipelines and processing frameworks (e.g., Apache Spark, Airflow)
Experience building analytical dashboards (Power BI, Tableau)
Strong analytical thinking and problem-solving skills
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