Senior ML Data Scientist, Apple Pay Analytics

Apple is where individual imaginations gather together committing to the values that lead to great work. Every new product we build service we create or Apple Store experience we deliver is the result of us making each others ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world changing lives for the better. Its the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in we can do the best work of our lives. Here youll do more than join something youll add something. At Apple extraordinary ideas have a way of becoming great products services and customer experiences very quickly. If you are an ambitious hands on seasoned senior analytics high-energy individual who is not afraid of challenges were looking for you to join the Wallet Payments u0026 Commerce Analytics organization to craft the future for the Apple Pay business.

Your recommendations will directly shape decisions at the highest levels while you partner with the extended data sciences u0026 data engineering to ensure reliable accessible data. We work fast and iteratively value open feedback and debate and balance teamwork with independent decision-making and smart risk-taking.

In this role youll be a strategic partner to senior leaders driving high-impact initiatives across multiple functions.n Youll turn complex business challenges into clear analytical approaches using advanced techniques to uncover insights measure performance and identify opportunities for growth and efficiency.n Develop time series forecasting models to predict critical business KPIs revenue trends and adoption patterns to support strategic planning and resource allocation.n Apply machine learning techniques to understand business growth drivers identify emerging trends and quantify the impact of key business initiatives.n Build analytical frameworks that combine statistical modeling and ML methods to deliver forward-looking insights to executive leadership.n Translate complex forecasting results and ML-driven analyses into clear business narratives that inform strategic decisions.n Leverage build GenAI applications to automate insights generation enhance data quality processes and devise new capabilities such as intelligent anomaly detection.n Design advanced ML models and capabilities to automate A/B test result interpretation generate experiment summary narratives and build intelligent systems that recommend optimal test designs.

5 years of demonstrated experience in a Machine Learning Engineer role.n Strong business acumen and the ability to think strategically and operationally.n Experience with time series forecasting methods and ML techniques for business analysis (regression classification clustering) to solve strategic business problems.n Be a self-starter driven accountable and a high-energy team player.n Proven experience being a thought partner to cross-functional business teams offering actionable data insights and recommendations.n Demonstrated ability to influence without authority.n Excellent communication skillsable to distill complex analysis into simple compelling narratives. Background in consulting or customer-facing fast-paced analytical environment.n Expertise with SQL R or Python and data visualization tools such as Tableau for full-stack data analysis insight synthesis and presentation.n Knowledge of and experience in leveraging Applied Statistical/ML techniques.n Bachelors degree in Economics Finance Statistics Mathematics Econometrics or Applied Social Sciences.

Demonstrated experience in an Analytics and Strategy role preferably in the payments/fintech domainn Ability to understand ambiguous and complex problems and design and execute analytical approaches and turn analysis into clear and concise takeaways that drive actionn Track record of leading organization-wide strategic initiatives or transformative analytics projectsn Masters degree in Economics Finance Statistics Mathematics Econometrics or Applied Social Sciences.