Senior Data Scientist - Hybrid

XPO•Boston, MA

1d•$125,000 - $150,000•Hybrid

About The Position

The Senior Data Scientist role at XPO involves leveraging machine learning, AI, statistical, and optimization methods to solve complex problems in areas such as network/route optimization, demand forecasting, and pricing/revenue modeling. The position requires designing, building, and evaluating models, and implementing them into software solutions. This role also involves exploring and applying cutting-edge AI techniques and statistical methods to identify opportunities for process improvements through analytics and automation. The Senior Data Scientist will conduct and present ad-hoc analyses to senior leaders, communicate with both technical and business audiences, and serve as a subject matter expert in applying AI techniques to logistics and transportation challenges. The role requires performing analytics ranging from predictive to prescriptive, aligning with AI maturity levels, and combining technical skills with business acumen to deliver 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
Strong understanding of data volume and quality requirements for building AI/ML and optimization solutions
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
5+ years of hands-on experience developing and deploying optimization, forecasting, or predictive modeling solutions
Experience applying statistical modeling, machine learning, and/or optimization techniques to one or more applied domains, such as network/route optimization, demand forecasting, or price/revenue modeling
Experience with causal inference and measurement methods for analyzing the impact of models on business outcomes
Experience with reinforcement learning for optimization, decision-making, or 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 problems across domains such as network/route optimization, demand forecasting, and pricing/revenue modeling
Design, build, and evaluate models under the guidance of Lead and Principal scientists, and help implement them into in-house software solutions
Explore and apply 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 contributor in applying AI techniques to logistics and transportation challenges
Perform analytics ranging from predictive to prescriptive, 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