Lead Scientist, Data Science (Pricing Optimization) - Hybrid

XPO; Boston (MA); Hybrid; USD 129,000 - 162,000; Full time

Benefits offered by this job

Competitive compensation

Health benefits from day one

Life and disability insurance

Paid time off

Company holidays

401(k) with company match

Education assistance

Incentive plan

Job summary

XPO is seeking a Lead Scientist, Data Science (Pricing Optimization) in Boston with a hybrid work arrangement. You will lead AI/ML modeling for pricing, collaborate with data scientists and engineers, and translate complex analyses into clear business insights to optimize revenue.

The role requires a bachelor’s degree with 4+ years in data science or a related field, strong programming skills, and experience applying AI techniques to pricing and forecasting.

Qualifications

• 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.

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.

Skills

Data science experience

Programming languages

AI/ML familiarity

Communication skills

Education

Bachelor’s degree related field

Master’s degree in Computer Science/AI/Data Science

PhD in Computer Science/AI/Data Science

Job description

Career Opportunities: Lead Scientist, Data Science (Pricing Optimization) - Hybrid (389106)

Requisition ID389106-Posted09/15/2026-US

Please note that the following enhanced screening and interview requirements apply to this role: Virtual backgrounds or headphones / earbuds are not permitted during web-based interviews. Additionally, a minimum of one onsite, in person interview will be required as part of the application process. By choosing to apply, you acknowledge and agree to these requirements.

What you’ll need to succeed as a Lead Scientist, Data Science at XPO

• 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

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
• 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

About the Lead Scientist, Data Science job

Pay, benefits and more:

• 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

What you’ll do on a typical day:

• 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

Annual Salary Range: $129, 446 to $161,807. Actual compensation may vary due to factors such as experience and skill set.
In addition to base salary, employees may be eligible for a sign‑on bonus, annual and long‑term incentive awards, and an equity buyout award. This is an incentive‑based position, which may include bonuses, incentive or commission plans.

About XPO

XPO is a top ten global provider of transportation services, with a highly integrated network of people, technology and physical assets. At XPO, we look for employees who like a challenge and can communicate effectively in all situations. We want to leverage your skills and years of experience to drive positive results while ensuring a bright future for yourself and XPO. If you’re looking for a growth opportunity, join us at XPO.

We are proud to be an Equal Opportunity employer. Qualified applicants will receive consideration for employment without regard to race, sex, disability, veteran or other protected status.

All applicants who receive a conditional offer of employment may be required to take and pass a pre‑employment drug test.

The above statements are not an exhaustive list of all required responsibilities, duties and skills for this job classification.

Review XPO's candidate privacy statement here .