Senior Data Science Manager – Strategic Data Solutions

Apple, Inc.; Cambridge (MA); On-site; USD 191,000 - 288,000; Full time

Job summary

Apple is seeking a Senior Data Science Manager in Cambridge to lead a team delivering fraud analytics and decision automation at scale. You will own analyses, build pipelines, and set governance with ML engineering and business leaders.

You will mentor a team of senior data scientists, drive methodological rigor, and shape the analytical strategy while hands-on contributing to complex analyses and model improvements.

Qualifications

• Bachelor's degree in Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field.
• 6+ years of hands on experience in data science, analytics engineering, or similar technical analytics roles, including 1+ years leading data scientists as a people manager or technical lead.
• Advanced proficiency in SQL and Python with experience writing production quality code, along with working knowledge of data warehouses, data lakes, and distributed processing of large datasets
• Strong background in statistical analysis, experimentation, and causal inference, including designing approaches when a clean randomized test is not available
• Experience building and maintaining production data pipelines and analytics systems, with a demonstrated record of measurable business impact

Responsibilities

• Hire, grow, and lead a team of data scientists who combine analytics engineering with deep statistical expertise, raising analytical quality through methodology review and your own technical contributions
• Lead through influence, balancing hands on technical mentorship with the strategic judgment to deliver scalable, high impact outcomes
• Build and maintain production data pipelines and reusable data models that power fraud analytics and decision automation, providing architecture guidance while ensuring data integrity, accessibility, and consistency across systems
• Design and implement robust monitoring, alerting, and health check systems that track data quality and model performance in production, surfacing issues before they affect fraud decisions
• Define success metrics and drive experimentation, causal inference, and statistical analysis, including designing rigorous approaches where conventional A/B testing is impractical
• Personally lead the most ambiguous and high stakes investigations, such as emerging attack patterns, enforcement anomalies, and unexpected shifts in model performance, and translate them into well scoped analytical questions with clear decision criteria
• Partner with machine learning engineering leaders to power decision automation, and with program and operations leaders to align analytical priorities, using compelling data storytelling, visualizations, and narratives to turn findings into decisions

Skills

SQL

Python

Statistics

Data pipelines

Experimentation

Causal inference

Team leadership

Education

Bachelor's degree

Tools

dbt

Snowflake

Spark

Airflow

CI/CD

Version control

Automated testing

Job description

Senior Data Science Manager - Strategic Data Solutions

Cambridge, Massachusetts, United States Corporate Functions

Imagine what you could do here! The people here at Apple don't just create products - they build 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. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work.

Description

Apple's Strategic Data Solutions team protects customers and the business from fraud and abuse across retail, online payments, and devices, at a scale few organizations ever encounter. We are looking for a data science manager who brings the technical depth of a senior practitioner and the judgment of a people leader. You will lead a team of highly technical data scientists who pair analytics engineering with deep statistical expertise, building the data foundations that power fraud decisioning and the rigorous analysis that shows what is working. You will personally own the most consequential analyses, pipelines, and measurement frameworks, working directly with machine learning engineering and business leaders to define how success is measured, uncover what is driving shifts in adversarial behavior, and turn those insights into automated decisions that protect millions of customers.This role is designed for someone who wants both the scope to shape a team and the opportunity to stay close to the hardest technical problems. You will spend a meaningful share of your time on hands on analysis, pipeline development, and methodology review, and your own work will set the analytical standard for the team. We are looking for someone who actively uses AI to accelerate their own work and who will help the team adopt new tools and practices as the field evolves.

Responsibilities

• Hire, grow, and lead a team of data scientists who combine analytics engineering with deep statistical expertise, raising analytical quality through methodology review and your own technical contributions
• Lead through influence, balancing hands on technical mentorship with the strategic judgment to deliver scalable, high impact outcomes
• Build and maintain production data pipelines and reusable data models that power fraud analytics and decision automation, providing architecture guidance while ensuring data integrity, accessibility, and consistency across systems
• Design and implement robust monitoring, alerting, and health check systems that track data quality and model performance in production, surfacing issues before they affect fraud decisions
• Define success metrics and drive experimentation, causal inference, and statistical analysis, including designing rigorous approaches where conventional A/B testing is impractical
• Personally lead the most ambiguous and high stakes investigations, such as emerging attack patterns, enforcement anomalies, and unexpected shifts in model performance, and translate them into well scoped analytical questions with clear decision criteria
• Partner with machine learning engineering leaders to power decision automation, and with program and operations leaders to align analytical priorities, using compelling data storytelling, visualizations, and narratives to turn findings into decisions

Minimum Qualifications

• Bachelor's degree in Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative field
• 6+ years of hands on experience in data science, analytics engineering, or similar technical analytics roles, including 1+ years leading data scientists as a people manager or technical lead
• Advanced proficiency in SQL and Python with experience writing production quality code, along with working knowledge of data warehouses, data lakes, and distributed processing of large datasets
• Strong background in statistical analysis, experimentation, and causal inference, including designing approaches when a clean randomized test is not available
• Experience building and maintaining production data pipelines and analytics systems, with a demonstrated record of measurable business impact

Preferred Qualifications

• Experience in fraud, risk, trust and safety, payments, or other adversarial domains
• Experience building and maintaining data transformation pipelines in dbt, including modular model design, testing, documentation, and version controlled development practices
• Familiarity with modern data platforms such as Snowflake, Spark, and Airflow, and fluency in software development lifecycle practices, including CI/CD, version control, and automated testing
• Track record of building analytics frameworks or tools adopted beyond your immediate team
• Expertise in data storytelling, including stakeholder ready visualizations and narratives that influence senior leadership decisions, along with a commitment to building inclusive teams that value diverse perspectives

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 $191,300 and $287,800, 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 seek to promote 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.

At Apple, we believe accessibility is a fundamental human right. You'll find that idea reflected in everything here - in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple's workplace.

Learn about reasonable accommodations for job applicants.

Apple accepts applications to this posting on an ongoing basis.