Director, Data Science - Earnings Innovation & Automation

About the role

Lead the transformation of earnings through advanced data science, automation, and innovation. As Director, you’ll drive high-impact analytical solutions, shape data strategy, and scale machine learning capabilities across the business.

About the Independent Contractor (Spark Driver) Earnings Team: Our team is responsible for the seamless calculation, disbursement, and reporting of independent contractor earnings & tax processes worldwide. We operate with a focus on compliance, data integrity, and continuous improvement, directly impacting both company performance and the experience of our global contractor network. This role is pivotal in setting best practices and driving operational rigor across the organization.

Responsibilities

• Define and lead AI/ML strategy for contractor earnings, tax, and compliance, identifying high-impact use cases such as anomaly detection, tax classification, and risk monitoring.
• Build and lead a high-performing data science “tiger team” to rapidly prototype, test, and scale innovative solutions across earnings and compliance domains.
• Develop intelligent automation and insights using ML and GenAI to improve accuracy, reduce manual effort, and enhance contractor and stakeholder experience.
• Embed compliance and governance into AI solutions by ensuring models are transparent, auditable, and aligned with regulatory requirements in partnership with Compliance and Governance leaders.
• Scale solutions into production by collaborating with Product, Engineering, and Operations to deliver measurable impact (e.g., reduced errors, lower risk, increased efficiency).

Requirements

• 10–12+ years of experience in data science, ML, or AI, with 3–5+ years leading high-performing teams.
• Strong track record of building and scaling production-grade ML/AI solutions in complex environments.
• Deep technical expertise in Python, SQL, and modern ML frameworks (e.g., TensorFlow, PyTorch).
• Experience in fintech, payments, tax, or compliance-heavy domains (preferred).
• Hands-on experience with GenAI/LLMs and applying them to real-world business problems.
• Strong understanding of model governance, explainability, and risk management.
• Ability to operate in ambiguity, influence cross-functional stakeholders, and drive outcomes at scale.

Qualifications

• Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years' experience in an analytics related field.
• Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field.
• 8 years' experience in an analytics or related field.

Skills

• Data science, machine learning, optimization models.
• PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics.
• Successful completion of one or more assessments in Python, Spark, Scala, or R.
• Supervisory experience.
• Using open source frameworks (for example, scikit learn, tensorflow, torch).

Benefits

• Competitive pay as well as performance-based bonus awards.
• Additional compensation includes annual or quarterly performance bonuses.
• Additional compensation for certain positions may also include : Stock.

Pay

The annual salary range for this position is $130,000.00 - $260,000.00 in Bentonville, Arkansas US-30099, $169,000.00 - $338,000.00 in Sunnyvale, California US-11807, $156,000.00 - $312,000.00 in Hoboken, New Jersey US-10279 | Bellevue, Washington US-11075.

Schedule

Not specified.