Senior Scientist, Data Science - Hybrid

XPO•Boston, MA

136d•$106,383 - $132,978•Hybrid

About The Position

The Senior Scientist, Data Science role at XPO focuses on leveraging Machine Learning, AI, statistical, and/or optimization methods to solve problems in Pricing, Sales, and Finance to optimize company revenue. The position involves working with a team of data scientists and engineers to design, test, and implement models into in-house software solutions. The role requires being a thought leader for Data Science and Analytics, exploring cutting-edge AI techniques, and conducting ad-hoc analyses for senior leaders. The scientist will communicate with both technical and business audiences, serve as a subject matter expert in applying AI to logistics and transportation challenges, and use advanced data science methods to enhance business performance. The role also involves performing analytics from predictive to prescriptive and cognitive, aligning with AI maturity levels, and combining technical skills with business acumen for real-world impact.

Requirements

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

Nice To Haves

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
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

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
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, 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