Staff Applied Scientist

Beacon Roofing Supply, Inc; Seattle (WA); On-site; USD 191,000 - 345,000; Full time

Benefits offered by this job

Annual performance bonus

Medical, dental, and vision insurance

401(k) with employer match

Paid time off and sick leave

Employee assistance program

Pet insurance

Job summary

A leading distribution company in Seattle is seeking an experienced Applied Scientist to develop forecasting and pricing models. The ideal candidate will have over 7 years of experience in Data Science, proficiency in Python, and strong SQL skills. Key responsibilities include collaborating with teams to integrate models into applications and driving data-driven strategies. This role offers a competitive salary range and extensive benefits, including equity incentives and wellness programs.

Qualifications

• 7+ years of experience in Applied Science / Data Science or Quantitative Research.
• Strong track record of deploying models into production.
• Hands-on experience in designing experiments and analyzing outcomes.

Responsibilities

• Develop and productionize forecasting, pricing, and supply chain models.
• Translate business problems into technical solutions.
• Collaborate with cross-functional teams to enhance model integration.

Skills

Time series forecasting

Python programming

SQL proficiency

Statistical analysis

Education

Advanced degree (MS or PhD) in a quantitative field

Tools

NumPy

pandas

PyTorch

TensorFlow

Job description

We’re looking for bold, entrepreneurial talent ready to help build something extraordinary — and reshape the future of building products distribution.

QXO is a publicly traded company founded by Brad Jacobs with the goal of building the market-leading company in the building products distribution industry. On April 30, 2025, QXO completed its first acquisition: Beacon Building Products, a leading distributor in the sector.

We are building a customer-focused, tech-enabled, and innovation-driven business that will scale rapidly through accretive M&A, organic growth, and greenfield expansion. Our strategy is rooted in delivering exceptional customer experiences, improving operational efficiency, and leveraging data, digital tools, and AI to modernize a historically under-digitized industry.

What you’ll do:

Modeling & Research

• 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
  • 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.

What you’ll bring:

Required

• 7+ years of experience in Applied Science / Data Science / Quantitative Research, with a strong record of shipping models into production.
• Deep expertise in one or more of the following:
  • Time series forecasting
  • Pricing & revenue management
  • Supply chain / inventory / logistics modeling
  • Operations research / mathematical optimization
• Strong 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.

What you’ll earn

• Base pay range: $191,000 - $345,000
• Annual performance bonus
• Long term incentive (equity/stock)
• 401(k) with employer match
• Medical, dental, and vision insurance
• PTO, company holidays, and parental leave
• Paid Time Off/Paid Sick Leave: Applicants can expect to accrue 15 days of paid time off during their first year (4.62 hours for every 80 hours worked) and increased accruals after five years of service.
• Paid training and certifications
• Legal assistance and identity protection
• Pet insurance
• Employee assistance program (EAP)

QXO is an Equal Opportunity Employer. We value diversity and do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, or any other protected status.

To comply with Pay Transparency laws, employers must disclose an annual salary range. Actual offers depend on factors such as location, experience, skills, and market data. This position may also offer variable compensation.

Please contact [e-mail] if you have any questions related to this job posting.