Finance AI Analyst
About The Position
The Finance AI Analyst designs and deploys AI/ML-driven analytics solutions within the Finance franchise of Enterprise Analytics. The role combines data engineering skills and applied AI/ML experience to translate business requirements into intelligent, automated insights for finance use cases. The analyst builds and maintains models and pipelines, develops data models in Snowflake, and troubleshoots data across the Enterprise Data Warehouse. They partner with Finance stakeholders to identify opportunities, integrate emerging AI tools, and establish practices for model monitoring, versioning, and governance.
Requirements
- At least 2 years of experience in data engineering, analytics engineering, or applied AI/ML roles.
- Strong SQL proficiency.
- Experience with Snowflake; Snowpark, Cortex AI, and ML functions are preferred.
- Experience building and deploying ML models using Python or a similar language.
- Ability to debug end-to-end data flows in a data warehouse environment and identify breakpoints in staging, transformation, and presentation layers.
- Familiarity with finance data domains such as GL, AP, AR, fixed assets, and cost accounting, or with SAP Finance.
- Experience with BI tools.
- Strong communication skills and ability to present AI concepts to non-technical finance stakeholders.
- Bachelor's degree in finance, computer science, mathematics, information systems, or business.
Nice To Haves
- Hands-on Snowflake experience with Snowpark, Cortex AI, or ML functions.
- Experience with Tableau.
- Experience with LLM-based applications, RAG architectures, or Snowflake Cortex Agents.
- Knowledge of finance portfolio management, FP&A, or treasury analytics.
- Familiarity with SDLC and CI/CD for data/ML pipelines.
Responsibilities
- Design, build, and maintain AI/ML models and pipelines for finance analytics use cases, including forecasting, anomaly detection, classification, and NLP on financial documents.
- Develop and optimize data models in Snowflake, leveraging Cortex or equivalent AI functions.
- Debug and troubleshoot data models across the Enterprise Data Warehouse stack by tracing data lineage, validating transformations, and resolving discrepancies at the model layer.
- Partner with Finance stakeholders to identify high-impact AI opportunities and translate them into production-grade solutions.
- Evaluate and integrate emerging AI tools, including LLMs, generative AI, and vector search, into the analytics ecosystem.
- Establish best practices for model monitoring, versioning, and governance.
Benefits
- Market-competitive compensation packages that include base pay, incentives, benefits, and equity.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
