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 other’s 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. It’s 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, you’ll do more than join something — you’ll 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, we're looking for you to join the Wallet, Payments & 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 & 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.

Minimum Qualifications

• • 5+ years of demonstrated experience in a Machine Learning Engineer role.

• • Strong business acumen and the ability to think strategically and operationally.

• • Experience with time series forecasting methods and ML techniques for business analysis (regression, classification, clustering) to solve strategic business problems.

• • Be a self-starter, driven, accountable and a high-energy team player.

• • Proven experience being a thought partner to cross-functional business teams offering actionable data insights and recommendations.

• • Demonstrated ability to influence without authority.

• • Excellent communication skills—able to distill complex analysis into simple, compelling narratives. Background in consulting or customer-facing, fast-paced analytical environment.

• • Expertise with SQL, R or Python and data visualization tools such as Tableau for full-stack data analysis, insight synthesis and presentation.

• • Knowledge of and experience in leveraging Applied Statistical/ML techniques.

• • Bachelor’s degree in Economics, Finance, Statistics, Mathematics, Econometrics, or Applied Social Sciences.

Preferred Qualifications

• • Demonstrated experience in an Analytics and Strategy role, preferably in the payments/fintech domain

• • Ability to understand ambiguous and complex problems and design and execute analytical approaches and turn analysis into clear and concise takeaways that drive action