Position SummaryThe Senior Director, Data and Analytics Transformation leads the strategy, modernization, and delivery of the company's enterprise data, reporting, and analytics capabilities. This leader will transform how the organization produces, governs, and consumes data, moving from manual, reactive reporting to automated, governed, forward-looking, AI-enabled insight. The role owns the roadmap for the Snowflake-based data platform and the analytics layer above it, builds and develops a high-performing team, and partners with executive leadership to ensure data drives decisions across the business.
The ideal candidate combines deep technical fluency (SQL, Python, Snowflake, Claude Agentic AI) with executive presence, problem solving skills, financial services domain expertise, and a track record of leading large-scale data transformation.
Duties and ResponsibilitiesStrategy and Transformation Leadership
- Define and execute a multi-year AI-first data and analytics transformation strategy and roadmap aligned to enterprise objectives, and secure executive sponsorship and funding
- Lead the modernization of reporting and analytics from manual and ad hoc processes to fully AI-enabled automated, scalable, self-service solutions
- Develop business cases and present proposals for automated data and reporting solutions to the executive team, quantifying ROI, risk reduction, and efficiency gains
- Champion a data-driven culture, presenting evidence-based recommendations that improve business processes, credit performance, and customer outcomes
Analytics, Reporting and Insight
- Set the vision and standards for executive and operational dashboards, and oversee the build and enhancement of reporting across the enterprise
- Drive the evolution of reporting from descriptive to predictive and prescriptive, including forecasting, trend analysis, and forward-looking performance indicators
- Partner with C-suite and business leaders to translate strategic questions into analytical solutions, ensuring outputs are actionable and tied to business objectives
- Provide oversight and quality review of high-visibility ad hoc analyses supporting senior management and board-level decision-making
Data Platform and Architecture
- Serve as the executive owner of the data and analytics platform strategy, including Snowflake architecture, data modeling standards, and BI tooling
- Lead the Enterprise Data Warehouse development effort, including technical requirements, prioritization, release planning, and user acceptance testing
- Partner with Engineering, IT, Security, and Product to ensure the platform is scalable, secure, cost-efficient, and performant
- Ensure end-to-end data reconciliation and lineage from source systems through the reporting presentation layer
AI and Automation
- Define and lead the strategy for applying AI-enabled tools to reporting, documentation, automation, and analytical workflows
- Guide the team in building reusable skills, markdown-based documentation and instruction files, and agents that improve productivity and quality
- Establish guardrails for responsible AI use, including data security, model risk, and human review standards
People Leadership
- Build, lead, coach, and develop a team of managers, analysts, and analytics engineers, setting clear goals and fostering a culture of curiosity and accountability
- Own hiring strategy, succession planning, and career pathways for the Data & Analytics function
- Manage budget, vendor relationships, and resource allocation across competing priorities
- Serve as a subject matter expert on current and future data infrastructure and mentor others in technical and analytical best practices
Minimum Qualifications- Bachelor's degree in Computer Science, Information Systems, Mathematics/Statistics, Data Science, Computational Finance, Economics, Engineering or equivalent experience
- 12+ years of progressive experience in data, data sciences, analytics, or reporting roles, including 5+ years leading teams
- Demonstrated success leading enterprise-scale data or analytics transformation initiatives
- Advanced fluency in SQL and Python for analysis and automation
- Extensive experience building and governing reporting with modern BI and data visualization tools (such as Sigma or Tableau)
- Hands-on experience with cloud data platforms, preferably Snowflake
- Experience applying AI-enabled productivity and analytics tools, including building skills, markdown files, and agents, to improve reporting, documentation, automation, and analytical workflows
- Financial services experience, with a strong understanding of financial and operational metrics
- Proven ability to communicate complex analytical concepts to executives and boards
Preferred Qualifications- Master's degree in Data Sciences, Analytics, Statistics, Economics, Computer Science, Engineering or a related field
- Deep Snowflake experience, including architecture, performance and cost optimization, and data sharing
- Consumer finance or lending experience (origination, servicing, collections, securitization or capital markets reporting)
- Advanced coding experience in languages such as Python, R, Spark, or Scala
- Experience with data governance frameworks, data catalogs, and modern data stack tooling (for example dbt, orchestration, and observability tools)
- Experience partnering with Finance, Credit Risk, Compliance, and Internal Audit functions
- Experience leveraging LLMs – Claude or copilot in accelerating development of data sciences, MIS, or visualization capabilities
Critical Competencies- Strategic vision: Sets direction, translates strategy into executable roadmaps, and links data investments to business value
- Transformation leadership: Leads change across teams and functions, and drives adoption of new tools, processes, and ways of working
- Domain expertise: Strong understanding of loan amortization methods and schedules, and of the metrics that drive consumer finance performance
- Executive influence: Communicates clearly and persuasively across all levels, from analysts to the C-suite and board
- Analytical rigor: Experience with complex data sets, with keen attention to detail and root cause analysis to resolve issues
- Curiosity and courage: Naturally curious, challenges the status quo, and is willing to reset entrenched practices
- Prioritization: Manages multiple competing priorities and makes sound trade-offs
- Talent development: Attracts, develops, and retains top talent
- Self-direction: Demonstrated ability to lead and perform effectively in a hybrid environment
Working Conditions
Hybrid environment, Monday‐Friday. Occasional evenings and weekends.
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