Staples Digital Solutions is building scalable AI-powered pricing, forecasting, optimization, and decision intelligence capabilities that help improve revenue, margin performance, customer value, and operational efficiency. This team partners across Product, Finance, Merchandising, Revenue Management, Digital, Sales, and Technology to turn complex commercial challenges into practical, measurable business outcomes.
As the Sr. Manager Data Science & Engineering-Pricing & Optimization you will lead the strategy, development, and delivery of enterprise-grade AI solutions that power smarter pricing and decision-making. You’ll manage AI Engineering and Data Engineering teams, guide technical roadmaps, and work closely with business and technology leaders to deliver solutions that drive growth, improve profitability, and create a better experience for customers and associates.
While this role will need to work our 4 day/week on-site hybrid schedule out of the Framingham, MA HQ facility, we will consider candidates willing to relocate and are able to consider providing relocation assistance.
What you’ll be doing:
- Lead the roadmap and delivery for pricing AI, forecasting, optimization, and decision intelligence solutions.
- Oversee development of capabilities such as price elasticity modeling, demand forecasting, promotion optimization, revenue optimization, and competitive pricing.
- Apply machine learning, statistical modeling, forecasting, and optimization techniques to solve complex business problems.
- Manage AI/ML platforms, MLOps processes, and cloud-based engineering solutions using technologies such as Databricks, Snowflake, and Azure AI.
- Establish performance metrics, monitor business impact, and drive continuous improvement of AI solutions.
- Partner with Product, Finance, Merchandising, Revenue Management, Digital, Sales, and Technology teams to prioritize work and deliver measurable business value.
- Champion AI-assisted software development practices that improve delivery speed, quality, and productivity.
- Manage team resources, budgets, priorities, and execution across multiple high-impact workstreams.
- Lead, coach, recruit, retain, and develop AI Engineering and Data Engineering talent while fostering a culture of innovation, accountability, and continuous improvement.
What you bring to the table:
- Strategic and technical leadership with the ability to connect AI engineering work to business goals.
- Strong commercial judgment and the ability to understand pricing, revenue, margin, and customer-value drivers.
- Analytical problem-solving skills and curiosity for using data to improve decision quality.
- Clear communication skills, including the ability to translate complex AI, analytics, and engineering concepts into business-focused recommendations.
- Cross-functional collaboration and influence across product, business, finance, sales, digital, and technology stakeholders.
- A people-first leadership style focused on coaching, talent development, accountability, and continuous improvement.
- An innovation mindset and comfort leading change in a fast-paced, evolving environment.
- Strong prioritization skills with the ability to balance multiple initiatives, risks, resources, and outcomes.
What’s needed- Basic Qualifications:
- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Economics, Information Systems, or related technical or quantitative field, or equivalent work experience.
- 10+ years of experience delivering enterprise-scale AI, data, analytics, or software engineering solutions.
- 5+ years of experience leading technical, analytics, AI, data engineering, or software engineering teams.
- 3+ years of experience supporting pricing, revenue management, forecasting, optimization, or retail analytics solutions.
- Experience developing, deploying, or supporting production AI/ML solutions.
- Experience using Python and SQL in AI, machine learning, data engineering, analytics, or software engineering environments.
- Experience working with cloud-based data, AI, or engineering platforms.
- Experience translating business requirements into technical solutions with measurable outcomes.
What’s needed- Preferred Qualifications:
- Master’s degree in Computer Science, Data Science, Engineering, Statistics, Operations Research, or a related quantitative, analytics, or technology discipline.
- Experience with price elasticity modeling, promotion optimization, demand forecasting, revenue optimization, or competitive pricing capabilities.
- Experience with Databricks, Snowflake, Azure AI, MLOps, or cloud-native architectures.
- Experience using AI-assisted development tools such as GitHub Copilot, Claude, ChatGPT, or similar technologies.
We Offer:
- Inclusive culture with associate-led Business Resource Groups
- 22 days of PTO and Holiday Schedule (7 observed paid holidays + 1 floating holiday)
- Online and Retail Discounts, Company Match 401(k), Physical and Mental Health Wellness programs, and more!
The salary range represents the expected compensation for this role at the time of posting. The specific base pay may be influenced by a variety of factors to include the candidate's experience, skill set, education, geography, business considerations, and internal equity. In addition to base pay, this role may be eligible for bonuses, or other forms of variable compensation.