This role pays more than
75%
of similar roles. Most pay
$126,800–$201,839
— the shaded band above.
At the midpoint, this role pays about
$199k
versus about
$164k
for comparable roles.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
1984 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1590 roles with salary data.
As an R&D Finance & Data Scientist, you will join the R&D Finance Tools & Analytics team to architect, build, and maintain financial data infrastructure and advanced analytical tooling. You will bridge the gap between financial operations and data science by automating mission-critical workflows, managing R&D headcount, Opex, and Capex spend, and improving data governance. Your daily work involves developing robust data pipelines, building LLM-driven agents using LangChain or LangGraph, and creating interactive Tableau dashboards for executive leadership. You will utilize a technical stack including SQL, Python, JavaScript, Dataiku, and Snowflake to solve complex problems in financial reconciliation, anomaly detection, and spend analysis. This role addresses the challenge of modernizing core finance operations by transforming manual processes into scalable, automated systems that provide granular visibility into product engineering investments and improve overall operating margin performance.
Architect and maintain the financial data infrastructure and automated workflows for R&D finance operations.
Build and deploy LLM-driven agents and machine learning models to automate reconciliations and variance analysis.
Develop and maintain scalable Tableau dashboards for spend analysis and executive leadership reviews.
Design and manage robust data pipelines and ETL processes using SQL and Python.
Enhance and govern multi-dimensional financial data models to provide visibility into product engineering investments.
Translate business requirements from stakeholders into technical specifications and prototypes.
Lead the rollout, documentation, and user enablement for new automated tools and capabilities.
Manage the multi-year technology roadmap for R&D finance systems and process re-engineering.
What we're looking for
BS in Computer Science, Software Engineering, Data Analytics, Information Systems, Finance/Economics with a technical focus, or equivalent practical experience.
5+ years of hands-on experience in full lifecycle software development, data engineering, and analytics in a finance or enterprise setting.
Advanced proficiency in SQL and Python for complex data extraction, pipeline orchestration, and analytical modeling.
Experience building enterprise-grade data flows and ETL/ELT pipelines in Dataiku and relational environments like Snowflake.
Proven track record of designing and maintaining high-performance Tableau dashboards for spend analytics and executive reviews.
Working knowledge of Machine Learning engineering and LLM development frameworks such as LangChain or LangGraph.
Experience with front-end web tools and scripting, such as JavaScript, to power internal workflows.
Demonstrated experience leading end-to-end project lifecycle deployments including scoping, architecture, and change management.
Experience in R&D/Engineering Finance or tech-industry financial operations (preferred).
Familiarity with RPA, enterprise ERP platforms like SAP or Workday, and data warehousing governance (preferred).
Basic understanding of core finance and accounting principles such as budgeting, forecasting, and Capex vs. Opex (preferred).