VP1 System Analyst (ML & NLP ), GMET
Core
Lead end-to-end delivery of enterprise data and analytics solutions leveraging traditional and modern Data architecture, with focus on design, governance, explainability, and regulatory acceptability for AI and NLP use cases.
Role type
VP1 System Analyst (ML & NLP)
Builds
Enterprise data platforms, analytics solutions, and AI/NLP-driven decisioning systems for financial services.
Domain
Financial Services / Data Engineering & AI Governance
Deliverable
production ML models | product features | dashboards & analysis
Required skills
Requirements analysis, solution design, test strategy review, risk management, product evaluation, root cause analysis, innovation leadership, data architecture design, AI design governance, regulatory compliance, stakeholder communication, process improvement.
Preferred skills
Financial Crime Analytics, Finance & Risk Analytics, Credit Scoring, Retail & Wholesale Datamarts, legacy EDW/Hadoop modernization, globally distributed team collaboration.
Technologies
Databricks, Snowflake, Azure Fabric, Google BigQuery, Apache Iceberg, Delta Lake, Apache Hudi, Spark, Trino/Presto, Hive, Informatica suite, Power BI, QlikSense, Python (Pandas, NumPy), SQL, BTEQ, GCFR.
Responsibilities
Lead end-to-end solution delivery for data and analytics across the full SDLC; Analyze business and regulatory requirements and translate them into scalable solution designs; Review and approve test strategies, functional test cases, and data validation approaches; Manage risks and issues related to scope, data quality, regulatory commitments, and delivery timelines; Participate in product and platform evaluations (RFPs, PoCs) for data, analytics, and AI tooling; Partner with production support team to conduct root cause analysis, resolution, and preventive controls; Drive productivity, efficiency & quality improvements across delivery and operational processes; Lead innovation and modernization initiatives, including data discovery, cataloguing, governance, and AI enablement; Design data architectures supporting NLP and AI-driven analytics; Define model inputs, outputs, validation criteria, and usage boundaries for regulated analytics.
Seniority
VP1, strategic leadership & hands-on architecture