Finance Data Scientist - Enablement

Summary

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and curiosity to your job and there's no telling what you could accomplish.

The FDT Enablement Engineer is a strategic advisor and hands-on enabler within our Catalyst Program, focused on driving Finance workforce transformation. This role is pivotal in evolving Finance teams from manual data preparers to AI-enabled decision partners by bridging the gap between business strategy and technology implementation.

Description

Your primary focus will be to guide Finance teams through their maturity journey-from file-based automation to intelligent AI and predictive models-regardless of their current technical expertise. You will empower them to effectively leverage capabilities ranging from data automation and business intelligence to advanced analytics, machine learning, and AI agent creation within a governed, compliant framework.

Responsibilities

Partner & Strategize: Partner with Finance leaders to assess their team's current delivery practices and technical maturity across the Finance AI & Data Capabilities maturity spectrum. Guide them in establishing actionable roadmaps for iterative improvement using tools, trainings, and best practices you help to provide.

Guide & Enable: Develop and deliver tailored roadmaps that outline capability improvements, training needs, and solution pathways in areas including:

Data fluency (SQL, data modeling, visualization)

Automation and workflow design

AI agent creation and management

Applied machine learning for forecasting and controls

Analytical storytelling and KPI communication

Governance and SOX compliance mindset

Educate & Up-skill: Lead engaging workshops and consultations through programs like the Data Wizard Academy to up-skill Finance teams on practical technical delivery concepts, including:

Transitioning from manual or local processes into to governed, automated workflows in Dataiku

SQL and Python fundamentals for Finance analysts

No-code/low-code entry points with visual recipes

Prompt engineering and agentic AI design for Finance use cases

Model explainability and human-in-the-loop validation

Agile methodologies and responsible innovation

Collaborate & Build: Work alongside engineering teams and Finance analysts to co-design and prototype accessible solutions such as:

Automated workflows connecting to certified data sources in Snowflake/EDW

Interactive dashboards with narrative storytelling

Finance-specific AI agents for data retrieval, summarization, and task execution

Predictive models for forecasting, anomaly detection, and operational efficiency

SOX-ready solutions with audit trails and version control

Champion Governance: Promote and ensure adherence to governance frameworks that enable innovation while maintaining compliance:

AI governance frameworks with access controls and audit trails

Certified data sources and reusable components

Version control and documentation standards

"Freedom to fail safely" culture with proper guardrails

Making SOX compliance and data security standards easy to understand and follow

Foster Culture: Act as a learning enthusiast, championing Finance's evolution from reactive reporting to proactive, predictive decision support. Build a "Finance Analytics Community" for peer support, knowledge sharing, and continuous improvement in data-driven decision-making.

Minimum Qualifications

Undergraduate degree in finance, economics, accounting or related disciplines

5+ years SQL and Python development experience, including data science and applied machine learning

Proven background in business analysis, technical consulting, product management, or similar role where you've guided technology-driven Finance or business initiatives through transformation

A rare ability to act as a "translator," making complex technical concepts (data warehousing, automation, ML, AI agents) accessible and relevant to Finance professionals with varying technical backgrounds

Demonstrated experience in stakeholder management with Finance leaders, with the ability to influence and build trust at all organizational levels

Experience in organizational transformation, change management, or digital capability-building programs, particularly moving teams from manual/Excel-based processes to automated, governed workflows

Understanding of Finance controls, compliance requirements (e.g., SOX), and the need for audit trails in analytical environments

Preferred Qualifications

Hands-on familiarity with enterprise data platforms like Dataiku, Snowflake/EDW, and data visualization tools (Tableau, Power BI, or similar)

Experience with no-code/low-code platforms and visual recipe builders that enable business user adoption

Understanding of AI agent creation, prompt engineering, and LLM fine-tuning for domain-specific applications

Demonstrated expertise managing code promot