Apply now: Data Scientist, Audience & Growth, Hybrid - New York, NY. Start date is ASAP for this contract position.
Job Title: Data Scientist, Audience & Growth
Location-Type: Hybrid - New York, NY (must currently permanently reside within 50 miles of NYC)
Start Date: ASAP
Duration: Contract - 6 months
Compensation Range: $75-80/hr W2
Benefits: Eligible for Health, Dental, Vision, and 401K
Visa Sponsorship: Not eligible for visa sponsorship
Job Description:
The client is seeking a mid-level Data Scientist to serve as the organization's central data resource, building out a foundational customer model and enabling data-driven decision-making across Retail, Digital, and Marketing teams.
Job Summary
•Design and build a customer segmentation model that synthesizes behavioral, transactional, and demographic data across multiple customer and user datasets
•Translate segmentation model outputs into actionable audience profiles and cohorts that can be operationalized by marketing and digital teams
•Analyze patterns across the customer lifecycle, including awareness, acquisition, engagement, lapse, and reactivation, to surface audience and revenue growth opportunities
•Partner with stakeholders across Retail, Digital, and Marketing to frame business questions and deliver data-driven recommendations on pricing, experience, and communication strategies
•Design and implement an experimentation framework for testing marketing campaigns, digital experiences, and activation offers, including defining success metrics and ensuring statistical validity
•Build dashboards and reports that make key metrics accessible to non-technical partners and leadership
•Maintain and iterate on segmentation models and reporting as audience strategy evolves over time
Minimum Requirements:
•3-5 years of experience in a data science role
•Strong background in customer data, including demonstrated experience building segmentation models such as clustering and RFM analysis
•Proficiency in Python or R, and SQL
•Solid understanding of customer KPIs including LTV, churn, and retention, with hands-on experience applying them in a business context
•Ability to communicate complex data findings clearly to non-technical stakeholders and leadership across multiple departments
•Experience with A/B testing and experimental design, including sample sizing and statistical inference
Preferred Qualifications:
•Deep familiarity with customer data spanning retail, membership, or a recurring-funnel business model
•Experience with BigQuery or Google Cloud Platform
•Experience with dbt, Dataform, or similar data transformation tools
•Experience with Looker or comparable BI tools
•Experience with Git or similar source version control tools
