Economist, ML Data Scientist - Data Solutions & Initiatives

Summary

Posted: Nov 11, 2024
Weekly Hours: 40
Role Number:200578155

The people here at Apple don't just create products - they create the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. We work in a startup atmosphere where individuals take ownership and have significant impact on the final product. We are a dynamic team within Apple’s Worldwide Sales organization, Data Solutions & Initiatives—focused on driving innovation through product design, engineering, and portfolio management. We are seeking a highly skilled and adaptable Economist/ML Data Scientist, who is a proactive self-starter, eager to learn, and excels in working with cross-functional teams to deliver insights and analytics to support our Sales and Sales Finance organizations. The ideal candidate will be responsible for evaluating and optimizing machine learning models—particularly those related to sales forecasting and demand prediction—developing key performance metrics, and conducting in-depth failure analysis. This role requires expertise in machine learning algorithms, data processing pipelines, and model optimization techniques, as well as proficiency in tools such as Python, R, SQL, and data visualization platforms. In addition to strong technical abilities, this role demands exceptional presentation and communication skills. You will effectively summarize and communicate complex model features, results, and predictions to business stakeholders and executives, helping to translate insights into actionable business decisions. Your work will play a pivotal role in forecasting and monitoring sales demand, and guiding investment decisions that drive measurable results.

Description

Data Science, Machine Learning & Storytelling Your responsibilities will include: * Collaborate with cross-functional teams—including machine learning engineers, product managers, and program managers—to plan, design, build, and deploy scalable data models and machine learning solutions. * Analyze large-scale sales and finance datasets to extract insights and troubleshoot forecasting models, ensuring accuracy and alignment with business goals. * Implement metrics to measure model performance and effectiveness, driving continuous improvements in prediction accuracy and decision-making. * Conduct research to develop advanced decision-making systems and assess the impact of new demand-generation programs. * Communicate complex data insights and model outcomes to stakeholders through clear data storytelling, ensuring findings are actionable and understandable. * Build and maintain internal visualization tools to support data-driven decisions within the Sales and Finance teams.

Minimum Qualifications

• PhD in Economics, Operations Research, Marketing Science or related field required.
• 5+ years experience applying econometric models required.
• Strong background in statistics, econometrics, operations research, or quantitative marketing.
• Expert R/Python programmer also proficient in other languages important to the ETL data pipeline (e.g. SQL).
• Expertise in data wrangling and developing data visualizations & reporting with toolings such as Tableau, Superset, AWS etc.
• Experience crafting, conducting, analyzing, and interpreting experiments and investigations.
• Ability to share results with a non-technical audience and advancing multiple projects at once on a tight schedule.
• Outstanding verbal and written communication skills, along with exceptional presentation skills.

Preferred Qualifications

• Experience in in-depth analysis of machine learning model failures
• Experience with machine learning interpretability methods.
• Experience in design/development of complex decision-making systems
• Detail-oriented to keep track of and understand the workings of complex algorithms.
• Self-motivated and curious with creative and critical thinking capabilities to improve data quality evaluation methods for diverse and complex data annotation programs.
• Ability to operate comfortably and effectively in a fast-paced, highly cross-functional, rapidly changing environment and self manage and work independently with dynamic requirements and priorities.

Pay & Benefits

• At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $207,800 and $312,200, and your base pay will depend on your skills, qualifications, experience, and location.
  
  Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
  
  Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
  

• Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.