Data Scientist

Role overview

ALICE + OLIVIA is looking for a Decision Science Engineer / Applied Data Scientist to design, operationalize, and take ownership of predictive models that improve decision-making across planning, merchandising and buying, customer analytics, and inventory management. The work centers on Palantir Foundry as the main analytics and deployment environment, with a focus on turning complex retail realities such as seasonality, product life cycles, allocation, replenishment, promotions, markdowns, and customer behavior into practical models that can be used in day-to-day workflows.

This is a highly collaborative position with regular interaction with planners, buyers, business users, and the teams building and using Foundry Workshop applications. The role sits inside the IT organization but supports the broader business, including DTC, wholesale, planning, and supply chain, and has clear exposure to senior business stakeholders. The emphasis is on applied data science, decision-support modeling, and bringing models into production, rather than reporting or core data engineering.

Key responsibilities

• Create, refine, and support predictive and statistical models for retail planning, buying, inventory, and demand forecasting.
• Deploy models in Palantir Foundry through Code Workbook and Code Repository, using Snowflake as the main source of data and keeping outputs production-ready and maintainable.
• Maintain and improve the analytical rules and assumptions used in planning and buying processes.
• Work closely with planning, buying, merchandising, and DTC stakeholders to turn business challenges into model-based recommendations.
• Partner with the Enterprise Applications team on Workshop app development so model outputs are presented clearly in business-facing Foundry tools.
• Develop models for customer segmentation, customer lifetime value, retention and churn, propensity, and campaign targeting within a Customer 360 context.
• Coordinate with Engineering, which owns pipelines and Snowflake ingestion, to make sure inputs are reliable, governed, and suitable for modeling.
• Enable human-in-the-loop decision making by allowing planners and buyers to review, question, and adjust outputs in real time.
• Check model results against business outcomes and historical performance, and work directly with end users to confirm accuracy and usefulness.
• Record model methods and assumptions so the work can be maintained and understood over time.

Requirements

• At least 4 to 8+ years of experience in data science, applied analytics, or predictive modeling.
• Strong background in predictive and statistical methods such as forecasting, optimization, regression, and classification.
• Advanced Python skills for analysis, modeling, and production-quality development.
• Strong SQL skills and practical experience with Snowflake or a comparable cloud data warehouse.
• Experience with Palantir Foundry is strongly preferred, including the Ontology layer, Code Workbook, Code Repository, and business-facing application workflows.
• Exposure to experiment design and causal inference.
• Experience with large-scale time-series forecasting.
• Retail experience is strongly preferred, especially familiarity with demand versus net sales, sell-through, markdowns, planning and buying processes, seasons, price groups, and store versus e-commerce dynamics.
• Comfort working with messy, real-world data and building models that support human judgment.
• Ability to work with semantic or ontology-based data structures.
• Strong communication and relationship-building skills for working directly with planners, buyers, and business stakeholders.
• Ownership mindset for continuously maintaining and improving models.
• Hands-on experience with Palantir Foundry Workshop applications.
• Background in wholesale or multi-channel retail, including DTC, wholesale, and brick-and-mortar planning cycles.
• Exposure to agent-based or AI-assisted analytics workflows.
• Experience in a formal governance or steering-committee-driven prioritization setup.
• Familiarity with Snowflake-native development approaches such as dbt, Snowpark, or similar tools.

Additional information

This role is part of the IT organization and reports to the VP of Information Technology. It works across Planning, Merchandising/Buying, DTC, and Supply Chain. Engineering is responsible for ETL, data pipelines, and Snowflake ingestion, while BI owns reporting and dashboards. This position owns predictive modeling, decision-support analytics, and model operationalization inside Palantir Foundry.

Priorities are managed through a cross-functional steering committee with representation from business stakeholders, giving the role structured visibility into commercial priorities and direct access to executive-level conversations from the start.

ALICE + OLIVIA describes this opportunity as a greenfield effort at an inflection point in how the company uses data for decisions. The goal is to build a lasting analytics capability that connects the Foundry investment to meaningful commercial results across the business. The company emphasizes that this is not an infrastructure maintenance or reporting role, but a chance to own a strategic function with close business contact and long-term impact.

Compensation

The base salary range for this New York or New Jersey position is $150,000 to $175,000 per year. Actual pay will depend on experience, qualifications, skill set, and internal equity considerations.

Location

New York, NY or Secaucus, NJ. The role is hybrid.