Senior Scientist, Data Science - Hybrid

XPO•Boston, MA

6d•Hybrid

About The Position

The Senior Scientist, Data Science applies machine learning, artificial intelligence, statistical, and optimization methods to problems in Pricing, Sales, and Finance to help optimize company revenue. The role partners with data scientists and engineers to design, test, and implement models in in-house software solutions, and serves as a thought leader for Data Science and Analytics across the organization. The position researches emerging AI techniques and statistical methods to identify process-improvement opportunities through analytics and automation. It also conducts and presents ad hoc analyses to senior leaders, communicates with technical and business-oriented audiences, and serves as a subject matter expert in applying AI to logistics and transportation challenges. Work may span predictive, prescriptive, and cognitive analytics, using methods such as machine learning, deep learning, and optimization to improve business performance and deliver practical impact.

Requirements

Bachelor’s degree or equivalent related work or military experience.
At least 2 years of experience in data science, operations research, or data analysis, focused on AI-driven analytics, statistical modeling, machine learning, forecasting, or optimization.
Experience with at least one programming language, such as Python, R, SQL, SAS, Spark, or Java, with practical applications in AI or ML projects.
Familiarity with AI techniques and machine learning algorithms, including supervised and unsupervised learning.
Strong communication skills and ability to translate complex AI concepts into clear business insights.

Nice To Haves

Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or another related quantitative discipline.
Master’s or PhD in Computer Science, AI, Data Science, or a related quantitative field.
Hands-on experience developing and deploying optimization solutions; the number of years is not specified in the posting.
5+ years of experience in pricing optimization and demand forecasting using 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.
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 to AI model validation.
Hands-on experience building and deploying AI models using supervised, unsupervised, and deep learning methods.

Responsibilities

Apply machine learning, AI, statistical, and optimization methods to challenges in Pricing, Sales, and Finance to optimize revenue.
Collaborate with data scientists and engineers to design, test, and implement models in in-house software solutions.
Provide thought leadership for Data Science and Analytics across the organization.
Research emerging AI techniques and statistical methods to identify opportunities for process improvement through analytics and automation.
Conduct and present ad hoc analyses to senior leaders in business and technology organizations.
Communicate findings and concepts to technical and business-oriented audiences.
Serve as a subject matter expert in applying AI techniques to logistics and transportation challenges.
Use advanced data science methods, including machine learning, deep learning, and optimization, to enhance business performance.
Perform predictive, prescriptive, and cognitive analytics aligned with project needs and AI maturity levels.
Combine technical AI and data science skills with business acumen to deliver practical business impact.