Lead Data Scientist

FASHIONPHILE is more than just fashion — we’re revolutionizing the ultra-luxury fashion experience in order to create a sustainable alternative that extends the life cycle of products and makes them more accessible to a diverse customer base. As we strive to become the world's most sought-after brand in luxury re-commerce, we know it's our team members who make it all happen! We value diversity in our people, perspectives, and products. For us, it's the only way to cultivate the creativity and innovation essential to achieving our mission and supporting our customers. We do this both in-person and through our digital omni-channel experiences. If you're someone who embraces change, is authentic, and wants to make an impact this is the place for you.

About the Opportunity:

FASHIONPHILE is seeking an exceptional Data Scientist to leverage both structured and unstructured data to address key business challenges. In this strategic role, you will partner with Merchandising Planning and Sales teams to resolve issues related to omni-channel inventory planning and demand forecasting for retail commerce. You’ll employ advanced statistical and advanced forecasting techniques to support short- and long-term inventory planning, optimize forecast accuracy, and provide strategic recommendations to senior management. Additionally, you will investigate sales trends, develop processes to understand customer journeys, and build models to enhance customer engagement, retention, and growth. Responsibilities include:

• Build and maintain advanced statistical, predictive and machine learning models to forecast luxury product demand at the SKU level across various channels and enhance business performance.
• Analyze forecast accuracy metrics, refine models through feature engineering and selection, and adjust based on feedback from sales, marketing, and management.
• Develop and implement a comprehensive demand forecast process integrated into the Sales and Operations Planning (S&OP) cycle.
• Investigate worldwide sales trends and opportunities to offer strategic recommendations on current and future demand.
• Develop data-driven inventory planning strategies that balance meeting customer demand with minimizing carrying costs.
• Analyze current inventory levels against predicted demand to ensure optimal product availability across channels.
• Implement algorithms to determine optimal buying/selling points, safety stock levels, and mitigate stockout risks using historical sales, customer journeys, lead times, and demand variability.
• Extract, clean, and transform large datasets from sources such as sales, customer behavior, marketing campaigns, and external market trends to solve complex business problems.
• Automate dashboards and reports to visualize key performance indicators (KPIs) and trends related to demand forecasting and inventory management, and other topics.
• Communicate complex findings using effective data visualization techniques to support strategic decision-making by senior management.
• Own transformation initiatives that focus on growth and influence teams and stakeholders to arrive at the right solutions for the business.
  
  

What We’re Looking For:

• Bachelor’s Degree in Math, Data Science, Statistics, or another analytical discipline (or equivalent experience)
• 6+ years’ in-depth experience in predictive analytics, building ML models and solving business problems using data insights; a focus on omnichannel forecasting models and inventory planning is a plus.
• Working knowledge of forecasting models and inventory optimization
• Proficiency in Python or R, SQL, and VBA, with strong data manipulation and analysis skills (e.g., using Pandas, NumPy, Scikit-learn).
• Familiarity with forecasting/modeling techniques (Bayesian statistics, regression, customer lifecycle value, A/B testing).
• Experience with time series forecasting methods (e.g., ARIMA, Exponential Smoothing, Prophet) and machine learning algorithms (e.g., Regression, Random Forest, Neural Networks) is a plus.
• Knowledge of cloud-based data platforms (AWS, Azure, GCP), data warehousing tools, and visualization/BI tools (e.g., Qlik Sense, Tableau).
• A good understanding of retail e-commerce & omni- channel operations, inventory management and demand forecasting.
  
  

What We Offer:

• Medical, Dental and Vision Coverage
• FSA options for Medical, Dependent Care & Commuter Benefits
• Paid Time off, Paid Sick Time, and Paid Holidays
• 401(k) with generous match program
• Free Life Insurance and AD&D
• Long Term Disability Insurance
• Employee Discount
  
  

Compensation:

• FASHIONPHILE reasonably expects the range to be $135,000.00 - $155,00.00 for this position in our Carlsbad, CA Location and offers an Annual Bonus Opportunity. Offered compensation will vary based on (a) location; (b) individual candidate qualifications; and (c) individual candidate experience. This post may be updated as new market data becomes available and is accurate as of the date of this posting. FASHIONPHILE reserves the right to modify this information at any time, subject to applicable law.

FASHIONPHILE is more than just fashion — we’re revolutionizing the ultra-luxury fashion experience in order to create a sustainable alternative that extends the life cycle of products and makes them more accessible to a diverse customer base. As we strive to become the world's most sought-after brand in luxury re-commerce, we know it's our team members who make it all happen! We value diversity in our people, perspectives, and products. For us, it's the only way to cultivate the creativity and innovation essential to achieving our mission and supporting our customers. We do this both in-person and through our digital omni-channel experiences. If you're someone who embraces change, is authentic, and wants to make an impact this is the place for you.

About the Opportunity:

FASHIONPHILE is seeking an exceptional Data Scientist to leverage both structured and unstructured data to address key business challenges. In this strategic role, you will partner with Merchandising Planning and Sales teams to resolve issues related to omni-channel inventory planning and demand forecasting for retail commerce. You’ll employ advanced statistical and advanced forecasting techniques to support short- and long-term inventory planning, optimize forecast accuracy, and provide strategic recommendations to senior management. Additionally, you will investigate sales trends, develop processes to understand customer journeys, and build models to enhance customer engagement, retention, and growth. Responsibilities include:

• Build and maintain advanced statistical, predictive and machine learning models to forecast luxury product demand at the SKU level across various channels and enhance business performance.
• Analyze forecast accuracy metrics, refine models through feature engineering and selection, and adjust based on feedback from sales, marketing, and management.
• Develop and implement a comprehensive demand forecast process integrated into the Sales and Operations Planning (S&OP) cycle.
• Investigate worldwide sales trends and opportunities to offer strategic recommendations on current and future demand.
• Develop data-driven inventory planning strategies that balance meeting customer demand with minimizing carrying costs.
• Analyze current inventory levels against predicted demand to ensure optimal product availability across channels.
• Implement algorithms to determine optimal buying/selling points, safety stock levels, and mitigate stockout risks using historical sales, customer journeys, lead times, and demand variability.
• Extract, clean, and transform large datasets from sources such as sales, customer behavior, marketing campaigns, and external market trends to solve complex business problems.
• Automate dashboards and reports to visualize key performance indicators (KPIs) and trends related to demand forecasting and inventory management, and other topics.
• Communicate complex findings using effective data visualization techniques to support strategic decision-making by senior management.
• Own transformation initiatives that focus on growth and influence teams and stakeholders to arrive at the right solutions for the business.
  
  

What We’re Looking For:

• Bachelor’s Degree in Math, Data Science, Statistics, or another analytical discipline (or equivalent experience)
• 6+ years’ in-depth experience in predictive analytics, building ML models and solving business problems using data insights; a focus on omnichannel forecasting models and inventory planning is a plus.
• Working knowledge of forecasting models and inventory optimization
• Proficiency in Python or R, SQL, and VBA, with strong data manipulation and analysis skills (e.g., using Pandas, NumPy, Scikit-learn).
• Familiarity with forecasting/modeling techniques (Bayesian statistics, regression, customer lifecycle value, A/B testing).
• Experience with time series forecasting methods (e.g., ARIMA, Exponential Smoothing, Prophet) and machine learning algorithms (e.g., Regression, Random Forest, Neural Networks) is a plus.
• Knowledge of cloud-based data platforms (AWS, Azure, GCP), data warehousing tools, and visualization/BI tools (e.g., Qlik Sense, Tableau).
• A good understanding of retail e-commerce & omni- channel operations, inventory management and demand forecasting.
  
  

What We Offer:

• Medical, Dental and Vision Coverage
• FSA options for Medical, Dependent Care & Commuter Benefits
• Paid Time off, Paid Sick Time, and Paid Holidays
• 401(k) with generous match program
• Free Life Insurance and AD&D
• Long Term Disability Insurance
• Employee Discount
  
  

Compensation:

• FASHIONPHILE reasonably expects the range to be $135,000.00 - $155,00.00 for this position in our Carlsbad, CA Location and offers an Annual Bonus Opportunity. Offered compensation will vary based on (a) location; (b) individual candidate qualifications; and (c) individual candidate experience. This post may be updated as new market data becomes available and is accurate as of the date of this posting. FASHIONPHILE reserves the right to modify this information at any time, subject to applicable law.