R&D Finance & Data Scientist

Imagine what you could do here. At Apple new ideas have a way of becoming extraordinary products services and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could accomplish. If you love thinking analytically and are passionate about using your financial knowledge to navigate challenges wed love to hear from you!nnAs an Ru0026D Finance u0026 Data Scientist you will play a critical role in architecting building and maintaining the financial data infrastructure and advanced analytical tooling that powers Apples Ru0026D Finance this role you will bridge the gap between financial operations and cutting-edge data scienceoptimizing how we plan track and manage Ru0026D Headcount Opex and Capex will combine deep financial acumen with hands-on technical expertise in SQL Python machine learning and Generative AI to eliminate operational friction improve data governance and deliver actionable executive intelligence. Partnering closely with cross-functional teams and the Finance Transformation Office your work will directly influence operating margin performance financial transparency and strategic product roadmaps in a dynamic fast-paced global environment.

The Ru0026D Finance Tools u0026 Analytics team is dedicated to modernizing and transforming core finance operations across the Ru0026D organization. We architect internal tools automate mission-critical workflows and build advanced analytics platforms that enable financial analysts and leadership to make faster data-backed this role you will take ownership of identifying manual bottlenecks and architecting scalable automated solutions across:nnFinancial Operations u0026 Control: Redesigning and automating expense management annual budget planning Purchase-to-Pay (P2P) workflows accounting close activities and headcount approval Analytics u0026 AI Enablement: Evaluating and deploying cutting-edge technologieswith a strong focus on Generative AI and automated monitoringto conduct financial reconciliations detect spend anomalies and enforce internal controls at Governance u0026 Product/LOB Modeling: Enhancing and maintaining the Line of Business (LOB) data models and multi-dimensional financial views to deliver granular reliable visibility into product engineering team thrives on innovation continuous improvement and cross-functional collaboration. You will work side-by-side with finance analysts business partners and engineering teams to champion standardizations and scalable best practices across the enterprise.

Systems u0026 Process Roadmap: Own prioritize and drive the multi-year technology and process re-engineering roadmap for Ru0026D Finance u0026 Development: Architect develop test deploy and maintain robust data pipelines internal web tools and automated workflows supporting day-to-day finance AI u0026 Intelligent Automation: Build fine-tune and deploy LLM-driven agents and ML models (using frameworks like LangGraph / LangChain) to automate complex reconciliations transaction categorization and variance Dashboards u0026 BI: Design and maintain scalable Tableau reporting suites for spend analysis forecast-vs-actual variance and executive leadership u0026 Reporting Models: Enhance optimize and govern the LOB reporting data model to ensure seamless financial visibility across product Alignment u0026 Requirements: Partner with SMEs business leads and finance analysts to gather business requirements translate them into technical specs/prototypes and drive Management u0026 Adoption: Lead rollouts documentation and user enablement for all newly developed tools and automated u0026 Compliance: Uphold the highest standard of data integrity confidentiality and governance around sensitive product roadmaps and financial data.

5 years of hands-on experience in full lifecycle software/tool development data engineering and analytics in a finance operations or enterprise analytics settingnBS in Computer Science Software Engineering Data Analytics Information Systems Finance/Economics with a technical focus or equivalent practical proficiency in SQL and Python for complex data extraction pipeline orchestration and analytical modeling across large-scale relational databases and data with front-end / web-based tools and scripting (e.g. JavaScript) to power internal financial -on expertise building enterprise-grade data flows ETL/ELT pipelines and advanced analytics in Dataiku and relational environments (e.g. FileMaker Snowflake or modern data warehouses).nProven track record designing building and maintaining high-performance interactive Tableau (or comparable BI) dashboards for spend analytics and executive-level knowledge of Machine Learning engineering and LLM development/orchestration frameworks (e.g. LangChain LangGraph AgentConnect).nDemonstrated ability to implement AI/ML capabilities for anomaly detection automated reconciliation and continuous control monitoringnDemonstrated experience leading end-to-end Project Lifecycle Deployments (scoping technical architecture prototyping testing deployment and change management).nExceptional communication skills with the ability to translate complex technical architectures into clear concise business narratives for executive with ambiguity high ownership and a proactive approach to pairing identified problems with viable technical solutions.

Direct experience within Ru0026D / Engineering Finance or tech-industry financial with RPA (Robotic Process Automation) enterprise ERP/financial planning platforms (e.g. SAP Workday Adaptive Insights) and enterprise data warehousing understanding of core finance and accounting principles (budgeting forecasting P2P lifecycle Capex vs. Opex headcount planning and general ledger/cost center structures).