Senior ML Data Scientist, Payments & Growth Analytics

AI Chopping Block, Inc.; Northern (KY); Hybrid; USD 150,000 - 230,000; Full time

Job summary

Apple is seeking a senior analytics professional to join the Wallet, Payments & Commerce Analytics organization. You will partner with data sciences and data engineering to ensure reliable, accessible data and to inform executive decisions.

You will build time series forecasts and ML models, translate results into clear business narratives, and help shape strategy with scalable analytics and GenAI-enabled insights.

Qualifications

• 5+ years experience as a Machine Learning Engineer.
• Strong business acumen with strategic and operational thinking.
• Experience with time series forecasting and ML techniques for business analysis.
• Self-starter, driven, accountable and a high-energy team player.
• Ability to influence cross-functional teams with actionable insights.
• Excellent communication; distill complex analyses into simple narratives.
• Proficiency in SQL, Python or R and Tableau for data visualization.
• Applied statistical/ML techniques knowledge.

Responsibilities

• Partner with senior leaders to drive high-impact initiatives.
• Translate complex business problems into analytical approaches and insights.
• Develop time series forecasting models to predict KPIs and revenue trends.
• Apply ML techniques to understand growth drivers and trends.
• Build frameworks combining stats and ML to deliver executive insights.
• Translate forecast results into clear business narratives.
• Leverage GenAI to automate insights and improve data quality.
• Design ML models to automate A/B test result interpretation.

Skills

Machine Learning

Time Series Forecasting

SQL

Python

R

Data Visualization

Communication

Cross-functional Collaboration

Strategic Thinking

Self-starter

Education

Bachelor's degree in Economics, Finance, Statistics, Mathematics, Econometrics, or Applied Social Sciences

Tools

Tableau

Job description

Apple is seeking a senior analytics professional to join the Wallet, Payments & Commerce Analytics organization. You will partner with data sciences and data engineering to ensure reliable, accessible data and to inform executive decisions.

You will build time series forecasts and ML models, translate results into clear business narratives, and help shape strategy with scalable analytics and GenAI-enabled insights.