Senior Scientist, Data Science - Hybrid

Responsibilities

• 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
• Work with a team of data scientists and engineers to design, test and implement models into in-house software solutions
• You will be 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, to identify opportunities to drive process improvements through analytics and automation
• 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, aligning with AI maturity levels based on project needs
• Combine technical skills in AI and data science with strong business acumen to deliver real-world impact at XPO

Qualifications

Minimum qualifications:

• Bachelor’s degree or equivalent related work or military experience
• 2 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

Preferred qualifications:

• 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
• years of hands-on experience in developing and deploying optimization solutions
• 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