Manager of AI & Data Science

The Manager, of AI & Data Science will architect and operationalize the data systems and predictive models that power experimentation, personalization, forecasting, and decision-making across Function of Beauty. This role defines how data flows into the business, ensuring unified, structured, and reliable inputs across DTC, retailer POS, CRM, and core business data environments. This role is foundational to FoB’s future operating model: moving from static reporting toward scalable, predictive, automated intelligence. By building pipelines, models, and decision systems, this role enables faster testing within DTC, more accurate retail launch sizing, and stronger forecasting accuracy. Functions & Responsibilities Data Architecture, Pipelines & Infrastructure
Build automated pipelines that ingest and unify DTC, POS, CRM, and product-level data into structured environments
Establish a central customer-level and subscription-level attribute structure for segmentation, retention, targeted testing, and product planning
Ensure datasets are model-ready, version-controlled, documented, and stable
Partner with Engineering to deploy pipelines into durable production environments with governance and uptime standards AI/ML Model Development
Build and maintain predictive models for:
Subscriber churn, cancellation risk, retention probability
Demand forecasting and replenishment timing
Loyalty segmentation & lifetime value
SKU-level recommendations
Define and maintain model performance metrics and continuously refine based on live results
Translate DTC learnings into predictive inputs that support:
Assortment decisions
Launch sizing
Replenishment planning
Quality risk monitoring
Identify early signals that determine whether innovation should scale or pause Analytics Automation
Deliver model outputs into usable business interfaces (dashboards, automated tables, alerts, APIs)
Build omni-channel measurement systems that unify retail + DTC performance
Automate recurring business intelligence views, including:
Subscriber health
Demand volumes and forecasts
Retention drivers and lift curves
Performance trajectories across channels
Convert predictive outputs into planning inputs used by Supply Chain, Finance, Labs, and Marketing Business Enablement & Strategic Influence
Create scalable data environments that enable partners to self-serve analyses
Package model outputs into actionable, business-friendly formats (e.g., risk scores, revenue sizing, cohort maps)
Partner with Consumer Insights to:
Validate datasets, cohort definitions, and sample sizes
Support experiment and testing design with structured inputs
Provide model-backed evidence that informs:
Targeting strategies
Forecasting and demand planning
Revenue sizing and risk assessments Qualifications
Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or related field
5-7 years experience in data science, AI/ML engineering, predictive analytics, or data systems architecture roles
Experience deploying production-level models (beyond prototyping)
CPG, consumer goods, and digital commerce experience strongly preferred Skills & Competencies
Advanced proficiency in statistical modeling, predictive analytics, and machine learning
Strong proficiency with SQL, Python, AWS tools (e.g., Redshift, Dynamo)
Experience designing automated data pipelines across multiple systems
Ability to define performance metrics and iterate based on real-time outcomes
Skilled at working cross-functionally and influencing decisions using model-based evidence
Ability to balance near-term execution with longer-term architecture planning This is a hybrid role that requires working in our NYC office Monday through Thursday. Function of Beauty is an Equal Opportunity Employer and are committed to creating an inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.