Senior Applied Scientist, Shipper Pricing

What you'll do

• Develop algorithms to optimize the trade-off between gross and net revenue during real-time bidding on shipper freight.
• Prototype and evaluate pricing solutions using statistical analysis and simulation techniques.
• Partner with engineering teams to deploy, productionize, and experimentally evaluate machine learning models.
• Analyze product performance data to identify improvement opportunities and determine causal factors.
• Establish standard methodologies for modeling, coding, analytics, and experimentation across the data science team.
• Communicate technical findings and insights to senior management and cross-functional stakeholders.
• Provide data-driven recommendations to guide product ideation and feature launch decisions.

What we're looking for

• Ph.D. or M.S. in Computer Science, Machine Learning, or Operations Research, or an equivalent technical background.
• 4+ years of experience developing and deploying machine learning models and optimization algorithms in production environments.
• Experience designing, executing, and analyzing experiments to measure the impact of changes to production ML models.
• Expertise in observational causal inference or statistical analysis.
• Proficiency in Python, SQL, and Spark.
• Experience developing neural network (NN) algorithms.
• Experience developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior.
• Experience in reinforcement learning and causal machine learning.