Lead Scientist, Data Science - Remote

XPO Logistics-posted 3 months ago
Full-time • Senior
Remote • Charlotte, NC
Truck Transportation
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As a Lead Scientist in Data Science at XPO, you will leverage Machine Learning, AI, statistical and/or optimization methods to solve various problems in Pricing, Sales, and Finance in order to optimize revenue for the company. You will work with a team of data scientists and engineers to design, test and implement models into in-house software solutions. This role requires you to be a thought leader for the practice of Data Science and Analytics across the organization, exploring and researching cutting-edge Artificial Intelligence techniques and statistical methods to identify opportunities for process improvements through analytics and automation. You will conduct and present ad-hoc analyses to senior leaders within the business and technology organizations, communicating effectively with both technical and business-oriented audiences. Additionally, you will serve as a subject matter expert in applying AI techniques to logistics and transportation challenges, leveraging advanced data science methods to enhance business performance.

  • Leverage Machine Learning, AI, statistical and/or optimization methods to solve various problems in Pricing, Sales, and Finance.
  • Work with a team of data scientists and engineers to design, test and implement models into in-house software solutions.
  • Serve as a thought leader for the practice of Data Science and Analytics across the organization.
  • Explore and research cutting-edge Artificial Intelligence techniques and statistical methods.
  • Conduct and present ad-hoc analyses to senior leaders within the business and technology organizations.
  • Communicate with technical and business-oriented audiences.
  • Serve as a subject matter expert in applying AI techniques to logistics and transportation challenges.
  • Leverage advanced data science methods, including machine learning, deep learning, and optimization, to enhance business performance.
  • Perform analytics ranging from predictive to prescriptive and cognitive.
  • Bachelor's degree or equivalent related work or military experience.
  • 4 years of experience in data science, operations research, or data analysis with a focus on AI-driven analytics, statistical modeling, machine learning, forecasting, or optimization.
  • Experience in at least one programming language such as Python, R, SQL, SAS, Spark, Java, etc., with practical applications in AI or ML projects.
  • Familiarity with AI techniques and machine learning algorithms, including supervised and unsupervised learning.
  • Strong communication skills with a knack for translating complex AI concepts into clear business insights.
  • Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or any related quantitative discipline.
  • A Master's or PhD in Computer Science, AI, Data Science, or a related quantitative field.
  • 5+ years' experience in pricing optimization, demand forecasting, utilizing statistical modeling, machine learning, and reinforcement learning techniques.
  • Experience with causal inference and measurement methods for analyzing the impact of pricing algorithms on revenue.
  • Experience with reinforcement learning for pricing optimization, decision-making, and consumer behavior modeling.
  • Proven track record of delivering AI-enabled insights that improved operations, financial performance, or customer experience.
  • Strong foundation in statistics including hypothesis testing, anomaly detection, and statistical inference, as applied in AI model validation.
  • Hands-on experience building and deploying AI models, including supervised, unsupervised, and deep learning methods.
  • Competitive compensation package.
  • Full health insurance benefits available on day one.
  • Life and disability insurance.
  • Earn up to 15 days of PTO over your first year.
  • 9 paid company holidays.
  • 401(k) option with company match.
  • Education assistance.
  • Opportunity to participate in a company incentive plan.
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