Lead Data Scientist

FASHIONPHILE

FASHIONPHILE is leading a revolution in ultra-luxury fashion, creating sustainable alternatives that extend product life cycles. The company values diversity and innovation in both in-person and digital omni-channel experiences. They aim to be the premier brand in luxury re-commerce.

In this role you can expect to have the responsibilities:

• Develop advanced statistical, predictive, and machine learning models for SKU-level demand forecasting across channels.
• Refine forecasting models and optimize accuracy with feature engineering and feedback analysis.
• Design and integrate a demand forecast process within the Sales and Operations Planning cycle.
• Analyze sales trends globally for strategic recommendations on demand.
• Create inventory planning strategies that balance demand fulfillment with cost efficiency.
• Monitor and adjust inventory levels according to predicted demand.
• Implement algorithms for optimal buying/selling and stock management using historical sales data and other variables.
• Extract and transform large datasets for complex problem-solving.
• Automate reports and dashboards for key performance indicator visualization.
• Present complex data findings to senior management for strategic decisions.
• Lead transformation initiatives focused on growth and guide teams to effective solutions.

This role comes with the following benefits:

• Medical, Dental, and Vision Coverage
• Flexible Spending Accounts for Medical, Dependent Care, and Commuter Benefits
• Paid Time Off, Paid Sick Time, and Paid Holidays
• 401(k) with matching program
• Free Life Insurance and AD&D
• Long Term Disability Insurance
• Employee Discount

This role requires you to have:

• Bachelor’s Degree in Math, Data Science, Statistics, or equivalent experience
• 6+ years in predictive analytics, machine learning model development
• Proficiency in Python, R, SQL, and VBA
• Experience with data manipulation using Pandas, NumPy, Scikit-learn
• Knowledge in forecasting models and inventory optimization

You would benefit from having:

• Understanding of retail e-commerce and omni-channel operations
• Experience with time series forecasting methods and machine learning algorithms
• Knowledge of cloud-based data platforms like AWS, Azure, or GCP
• Familiarity with data warehousing and visualization tools like Tableau

This role requires two days onsite per week in either Carlsbad, CA, or Downtown Los Angeles, with the rest of the time worked remotely.