Entry Level Financial Modeling Jobs in Austin, TX

Do you love the challenge of solving complex problems that can have a direct and meaningful impact on the company? Do you want to be part of a supportive team that's constantly learning and having fun while solving tough business problems? We'd love to talk to you if you do!
Join the Applied Data Solutions Program (ADSP) and make a positive impact on one of the most influential technology leaders in the industry. You'll be tasked with building sophisticated, scalable and robust architecture, tools, data products, and critical data pipelines that are optimized for rapid business intelligence, data analysis, and data science. You will work with teams across Apple, using data analysis and predictive modeling techniques, to define, build, deploy, and maintain end-to-end operational solutions that have a direct and measurable impact to the company and our customers. The enormous scale and complexity of the problems and our data present exciting opportunities for pushing the limits of existing data science methods.
Description
The ADSP provides entry-level talent with practical work experience through project-based rotations on various teams within Finance. Upon completion, ADSPs move into non-rotating technical roles within Apple. We have a variety of opportunities for software engineers, data scientists, and machine learning engineers. Responsibilities may include:
• Support our business partners and optimizes the customer experience by delivering data-driven solutions that mitigate fraud, improve security, and optimize efficiency.
• Work closely with Machine Learning Engineers and other Software Engineers to lead the design and implementation of scalable, easy-to-use systems and tools.
• Engage with stakeholders to translate ambiguous business problems into technical solutions, including finding opportunities, breaking them into solvable segments, defining requirements, assessing level of effort, etc.
• Work cooperatively to design data science-driven solutions, balancing the utility of tried-and-true techniques and the benefits of custom solutions.
• Develop self-service tools and automation to improve data engineering efficiency and self-service analytics.
• Create reporting and monitor decisioning quality to maintain operational and business metric health.
• Translate ambiguous business problems into technical solutions by working collaboratively with business partners.
• Develop, deploy, and operationally support machine-learning models that take real-time and forensic action against a variety of threats to Apple's ecosystem.
• Apply data science to core finance processes to automate and elevate capability, forecasting, accruals, accounting entries prep, IA process, risk mitigation, etc.
Minimum Qualifications
Undergraduate or graduate degree in Computer Science, Data Science, Data Analytics, Machine Learning or related field.
Proficient in at least one programming language (Python/Scala/Java preferred).
Practical experience (acquired through work, independent projects, or academic research) in deploying machine learning solutions to answer real-world questions.
Practical experience (acquired through work, independent projects, or academic research) with implementing data science-related applications in a programming language such as Python, Scala, or Java.
Effective communication skills to translate complex concepts and analysis into concise, business-focused solutions.
Previous Apple FDP or ADSP internship is required.
Preferred Qualifications
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact.
Experience with ML platform provisioning and optimization (e.g., Dataiku, Ray, GPU-based training environments).
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact.