Remote Data Science Manager: Scalable ML & Growth

Marketplace Operations Inc.; Wilmington (DE); Remote; USD 120,000 - 180,000; Full time

Job summary

Marketplace Operations Inc. is seeking a Data Science Manager to lead a growing team of data scientists, drive production-grade models and partner with stakeholders to turn data insights into impact.

In a remote role, you will balance hands-on modelling with strategic leadership, shaping methodologies, reviewing outputs, and ensuring models are deployed with measurable business value. The ideal candidate combines strong technical depth in predictive analytics with excellent communication and

Qualifications

• Experience managing and developing Data Scientists.
• Strong predictive modelling, machine learning and customer analytics.
• Experience deploying models to production with ML Ops.
• Excellent stakeholder management and communication skills.
• Product-minded with ability to build reusable capabilities.

Responsibilities

• <b>Commercial & Decision Science:</b> Identify high‑value opportunities and translate business problems into predictive models with commercial impact.
• <b>Scalable DS Products:</b> Develop reusable models scalable across products and use cases.
• <b>Production DS:</b> Deploy models with monitoring and retraining in production.
• <b>Business Partnership:</b> Build relationships with Marketing, Commercial, Analytics, Product and Engineering.
• <b>Team Leadership:</b> Coach and develop Data Scientists while ensuring quality and standards.

Skills

People management

Predictive modelling

Machine learning

Customer analytics

Python

SQL

Cloud-based DS environments

Stakeholder management

Communication

Product mindset

Commercial judgement

Tools

Python

SQL

Cloud platforms

Job description

Marketplace Operations Inc. is seeking a Data Science Manager to lead a growing team of data scientists, drive production-grade models and partner with stakeholders to turn data insights into impact.

In a remote role, you will balance hands-on modelling with strategic leadership, shaping methodologies, reviewing outputs, and ensuring models are deployed with measurable business value. The ideal candidate combines strong technical depth in predictive analytics with excellent communication and