Snr Manager – Data Science (Ref: 197505)

Forsyth Barnes; Virginia; On-site; USD 150,000 - 210,000; Full time

Job summary

Forsyth Barnes is partnering with a leading organization to appoint a Senior Manager – Data Science, Pricing Algorithms to lead a data science team in Richmond, Virginia, onsite four days a week.

You will design and implement pricing algorithms, optimization models and AI-driven solutions at scale, mentor 4–7 data scientists, and partner with Engineering, IT and Commercial teams to deploy production-ready models that drive margin and revenue.

Qualifications

• 6+ years in Data Science, Advanced Analytics or ML
• Experience leading Data Science teams
• Strong background in predictive models, optimization or pricing models
• Experience solving complex commercial or operational problems
• Proven ability to influence senior stakeholders through data-driven insights
• Excellent communication and leadership skills
• Experience deploying production AI/ML solutions

Responsibilities

• Lead and develop a team of 4–7 Data Scientists.
• Design advanced pricing algorithms and optimization models.
• Build AI-driven pricing solutions at scale.
• Develop ML models that respond to changing market conditions.
• Partner with Engineering, IT and Commercial teams to deploy production-ready solutions.
• Drive experimentation and measure business impact through A/B testing and analytics.
• Continuously optimize pricing strategies to improve commercial performance.
• Mentor technical talent and foster a high-performance culture.
• Present complex analytical findings to senior leadership and stakeholders.
• Deliver scalable AI solutions that generate significant business value.

Skills

Leadership

Data Science

Pricing/Optimization

Communication

Job description

Job Title: Senior Manager – Data Science, Pricing Algorithms (Ref: 197505)

Forsyth Barnes is partnering with a leading organization to appoint a Senior Manager – Data Science, Pricing Algorithms to lead a high-performing Data Science team responsible for developing advanced pricing algorithms and AI solutions that drive business strategy and commercial performance.

This is an exciting opportunity for an experienced Data Science leader with a strong background in machine learning, optimization and predictive modelling. You'll lead the development of intelligent pricing models that influence millions of pricing decisions, partnering closely with Engineering, Product and Commercial teams to deliver measurable business value.

Key Responsibilities

• Lead and develop a team of 4–7 Data Scientists.
• Design and implement advanced pricing algorithms and optimization models.
• Build AI-driven solutions that automate pricing decisions at scale.
• Develop machine learning models that respond to changing market conditions.
• Partner with Engineering, IT and Commercial teams to deploy production-ready solutions.
• Drive experimentation and measure business impact through A/B testing and analytics.
• Continuously optimize pricing strategies to improve commercial performance.
• Mentor and develop technical talent while fostering a high-performance culture.
• Present complex analytical findings to senior leadership and business stakeholders.
• Deliver scalable AI solutions that generate significant business value.

Required Experience

• 6+ years' experience within Data Science, Advanced Analytics or Machine Learning.
• Experience leading or mentoring Data Science teams.
• Strong background building predictive models, optimization algorithms or pricing models.
• Experience solving complex commercial or operational business problems.
• Proven ability to influence senior stakeholders through data-driven insights.
• Excellent communication and leadership skills.
• Experience deploying production AI or machine learning solutions.

Technical Knowledge

• Optimization & Mathematical Modelling.
• Artificial Intelligence.
• Experiment Design & A/B Testing.
• Software Engineering principles.

Please note: Applicants must be authorized to work in the United States. Sponsorship is not available for this position. This role requires onsite attendance in Richmond, Virginia, four days per week.