Senior Applied Scientist

About the role

QXO is a leading distributor and installer of building products serving an $800 billion market. The company's mission is to modernize the building products industry through advanced technology and a best-in-class customer experience. QXO is North America's largest distributor and installer of insulation, the second-largest distributor of roofing products, the second-largest publicly traded distributor of lumber and building materials, and the largest distributor of waterproofing products. The company is targeting $50 billion in annual revenue within the decade through accretive acquisitions and organic growth.

What you'll do

Modeling & Research — depending on your expertise, you may focus on some of the following areas:

Forecasting

• Build and productionize time series models for demand, sales, and inventory (e.g., hierarchical forecasting, intermittent demand, seasonality/trend modeling, multivariate forecasting).
• Develop approaches to handle sparse, volatile, and evolving data environments.

Pricing & Revenue

• Develop pricing models and policies, including elasticity estimation, margin optimization, and discounting/contract structures.
• Support pricing for quotes and BOMs, including guardrails, risk/margin checks, and complex B2B rules around bundling and substitution.

Supply Chain & Inventory

• Design models for inventory planning, replenishment, and allocation under real-world constraints (lead times, MOQs, service levels).
• Build tools to improve fill rates, reduce stockouts, and manage working capital.
• Formulate and solve optimization problems (linear, mixed-integer, non-linear, heuristics/approximation) for routing, allocation, capacity, and network flows.
• Integrate optimization with forecasting/pricing models to support end-to-end decisions.

Across all areas, you'll

• Combine statistical methods, machine learning, and operations research techniques as appropriate.
• Stay current on relevant research and bring practical, scalable methods into production.

Decision Systems & Product Integration

• Translate messy business problems into clear technical formulations and evaluate alternative approaches.
• Work with engineers to turn models into robust services powering internal tools, APIs, and AI agents (e.g., quoting & BOM agents, pricing copilots, supply planning tools).
• Build or contribute to simulation and scenario analysis frameworks to test policies before rollout.
• Define and implement offline and online evaluation (experiments, policy evaluation, counterfactual analysis).

Data, Measurement & Experimentation

• Partner with data engineering to ensure data quality, structure, and accessibility for modeling.
• Define metrics for your domain (forecast accuracy, stockouts, margin impact, quote win rates, price realization, etc.).
• Design experiments and quasi-experiments to measure the business impact of new models and policies.
• Clearly communicate findings, trade-offs, and recommendations to stakeholders.

Collaboration & Leadership

• Work closely with Sales, Marketing, Supply Chain, Finance, and Product teams to understand constraints, workflows, and incentives.
• Collaborate with AI Engineers who will embed your models inside intelligent agents and applications.
• Mentor other scientists and engineers; elevate standards around methodology, code quality, and evaluation.
• Influence roadmap and strategy by highlighting long-term modeling opportunities and risks.

Required

• 2+ years of experience in Applied Science / Data Science / Quantitative Research, with a strong record of shipping models into production.
• Expertise in one or more of the following: time series forecasting; pricing & revenue management; supply chain / inventory / logistics modeling; operations research / mathematical optimization.
• Proficiency in Python and scientific computing libraries (NumPy, pandas, etc.).
• Solid SQL skills and experience working with modern data warehouses/lakehouses.
• Hands-on experience designing experiments, analyzing results, and working with ambiguous real-world data.
• Excellent communication skills and demonstrated ability to lead projects spanning multiple teams.

Preferred

• Prior experience in retail, B2B distribution, manufacturing, or the building materials / construction industry.
• Experience with revenue management, discounting, and contract/pricing architectures.
• Experience with supply chain planning systems (MRP/DRP, S&OP) and operational constraints.
• Familiarity with deep learning libraries (e.g., PyTorch, TensorFlow, JAX).
• Experience integrating models with downstream applications or AI agents, including considerations for latency, reliability, and interpretability.
• Experience with large-scale or distributed data/compute systems and ML platforms (MLOps, feature stores, model registries, CI/CD for models).
• Advanced degree (MS or PhD) in a quantitative field such as Statistics, Operations Research, Applied Mathematics, Computer Science, or a related discipline.

Pay

USD $159,000.00 - USD $287,000.00 /Yr.

Benefits

• 401(k) with employer match
• Medical, dental, and vision insurance
• PTO, company holidays, and parental leave
• Paid training and certifications
• Legal assistance and identity protection
• Pet insurance
• Employee assistance program (EAP)