Data Scientist III, Customer Strategy

Benefits

Parental leave

6 weeks From the posting source checked Jun 20, 2026

Non-birth-parent leave

6 weeks From the posting source checked Jun 20, 2026

Family-building benefits

• Fertility benefits: Offered From the posting source checked Jun 20, 2026
• Adoption assistance: Offered From the posting source checked Jun 20, 2026
• Surrogacy assistance: Offered From the posting source checked Jun 20, 2026

Mental health support

Offered From the posting source checked Jun 20, 2026

Relocation assistance

Not verified

Childcare support

Offered From the posting source checked Jun 20, 2026

Learning budget

Not verified

Verification

Source-linked checked Jun 7, 2026

Salary

$175K-$237K From the posting source checked Jun 20, 2026

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

84% above the BLS role benchmark for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Data Scientist III, Customer Strategy New York, New York, USA Shopbop and Zappos are looking for a customer-obsessed Data Scientist to join the Customer Analytics organization. This role will be at the center of how we understand, reach, and serve our customers across every channel, not as a support function, but as a driving force behind our customer strategy. You will build the models that power personalization across sites, email, push, and paid media. You will design the causal frameworks that prove what's actually working versus what just looks like it is. You will apply machine learning, LLMs, and advanced optimization techniques to move us from intuition-driven decisions to evidence-driven ones at scale, across Shopbop and Zappos. The right candidate combines deep technical skills in machine learning and causal inference with genuine curiosity about customer behavior and retail dynamics. They thrive in ambiguity, move fluidly between model development and business strategy, and communicate complex findings clearly to both technical and non-technical audiences. They should have a collaborative mindset that enables them to work effectively across Lifecycle Marketing, Merchandising, Product, Engineering, and other cross-functional partners. This position sits within the Customer Experience organization. Key job responsibilities Design, build, and iterate on customer segmentation models that drive product recommendations, content ranking, intent detection, and customer-specific experiences on site, in email, and in push notifications across Shopbop and Zappos. Apply advanced optimization techniques - including uplift modeling, to improve real-time decisioning across marketing, digital, and channel experiences. Apply causal inference methods grounded in

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