Principal Data Scientist — Retail Forecasting & Merchandising

BICP; Carlsbad (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

BICP is seeking a Principal Data Scientist to work embedded with a leading apparel and lifestyle brand in the San Diego area. You will own end-to-end data science initiatives across forecasting, inventory optimization, and merchandising, translating complex analyses into actionable business recommendations.

This hands-on role combines technical leadership with mentoring, collaborating with product, engineering, and business teams to productionize models, measure impact, and drive adoption.

Qualifications

• 8+ years of data science or applied ML experience with principal-level ownership.
• Direct retail/apparel experience and hands-on demand planning.
• Proven track record delivering production forecasting/optimization.
• Ability to translate forecasts into buying, assortment, and inventory decisions.
• Strong communication and stakeholder management.

Responsibilities

• Lead data science initiatives across forecasting, inventory optimization, and merchandising.
• Partner with planners, merchants, and business teams to align workflows.
• Assess data and methods to identify gaps with measurable value.
• Build models accounting for seasonality, promotions, and product lifecycles.
• Translate analyses into clear recommendations for business stakeholders.
• Collaborate with product and engineering to productionize models.
• Mentor other data scientists and strengthen analytical practices.

Skills

Retail experience

Forecasting

Time-series modeling

Python

SQL

Stakeholder management

Mentorship

Productionization

Job description

BICP is seeking a Principal Data Scientist to work embedded with a leading apparel and lifestyle brand in the San Diego area. You will own end-to-end data science initiatives across forecasting, inventory optimization, and merchandising, translating complex analyses into actionable business recommendations.

This hands-on role combines technical leadership with mentoring, collaborating with product, engineering, and business teams to productionize models, measure impact, and drive adoption.