Director of Data Science

Key Responsibilities

• Develop and maintain forecasting and predictive models supporting transportation use cases such as pricing, demand forecasting, capacity trends, service performance, and network dynamics.
• Build and scale the data science function, including hiring, onboarding, and managing direct reports as business needs evolve.
• Design and execute statistical modeling and experimentation, including hypothesis testing, A/B testing, and causal analysis to evaluate market and operational changes.
• Build optimization and decision support models that inform routing, capacity allocation, pricing strategy, and operational trade-offs.
• Lead signal development for transportation intelligence products, transforming raw transactional and network data into scalable, reliable indicators and indices.
• Establish and lead model validation, performance monitoring, and governance frameworks to ensure stability, accuracy, and trustworthiness of production models.
• Partner closely with product, analytics, and engineering teams to translate transportation domain needs into analytically sound, production ready models.
• Document methodologies, assumptions, and limitations to support transparency, internal review, and customer facing confidence in intelligence outputs.
• Continuously evaluate new data sources, modeling approaches, and techniques relevant to transportation, logistics, and network-based intelligence.

Required Qualifications

• A Master's degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or another relevant quantitative discipline is required.
• 5–7 years of professional experience in data science, applied statistics, or quantitative analytics.
• Strong experience with forecasting, predictive modeling, and statistical analysis in applied business contexts.
• Demonstrated ability to build models that support decision making, optimization, or market intelligence.
• Strong Python and SQL skills and experience working with large, complex datasets.
• Experience validating models and monitoring performance in production environments.
• Direct experience with model governance frameworks.
• Ability to clearly communicate quantitative insights to both technical and non‑technical stakeholders.

Preferred Qualifications

• Experience working with transportation, logistics, supply chain, or network-based data.
• Strong expertise in Regression & tree-based models (e.g., XGBoost, Random Forest)
• Time series forecasting (e.g., SARIMAX, Prophet, TFT)
• Statistical modeling of skewed distributions (e.g., log-normal, gamma)
• 2 years in a leadership or people‑management capacity
• Deep understanding of freight market dynamics, including the interaction between spot and contract pricing, broker and carrier economics, and the impact of capacity cycles and seasonality on market behavior.
• Familiarity with time‑series modeling, signal processing, or index construction.
• Experience supporting intelligence, analytics, or data products used by external customers.
• Experience working with large-scale datasets in cloud environments and data pipelines (e.g., Snowflake, AWS, Sagemaker).

Pay

We offer Medical, Dental, Vision, Paid Time Off, 401k and much more.