Remote ML Manager — Workforce Forecasting & Routing

Monzo; Germany (OH); Hybrid; USD 153,000 - 197,000; Full time

Benefits offered by this job

Relocation assistance

Visa sponsorship

Learning budget

Home office setup support

MacBook provided

Job summary

Monzo is seeking a hands-on senior ML leader to head the Workforce Management ML effort. You will shape strategy, design and deliver production forecasting, routing and time-to-completion models, and collaborate with product squads across data, engineering and operations.

You should have recent hands-on ML experience, able to coach ML scientists, explain complex ideas to both technical and non-technical stakeholders, and drive pragmatic, high-quality ML solutions that improve customer outcomes.

Qualifications

• Hands-on ML practitioner with leadership experience.
• Strong foundations in ML, statistics, forecasting, optimisation or operations research.
• Experience shipping ML systems in production.
• Ability explain ML ideas clearly to technical and non-technical people.
• Coaching others and potential people management experience or willingness to step into management.
• Able to navigate ambiguous problem spaces with pragmatic ML solutions.
• Customer outcomes driven ML initiatives.

Responsibilities

• Shape the ML strategy for Workforce Management.
• Lead design and delivery of production ML systems for forecasting, routing, assignment, escalation and time‑to‑completion prediction.
• Stay close to technical details and validate modeling approaches.
• Collaborate with Product, Engineering, Data and Operations leaders to translate problems into ML solutions.
• Coach and develop Machine Learning Scientists.
• Establish strong technical standards, documentation and monitoring.
• Contribute to scaling ML systems in production.

Skills

Machine Learning

Forecasting

Operations Research

Leadership

Production ML

Job description

Monzo is seeking a hands-on senior ML leader to head the Workforce Management ML effort. You will shape strategy, design and deliver production forecasting, routing and time-to-completion models, and collaborate with product squads across data, engineering and operations.

You should have recent hands-on ML experience, able to coach ML scientists, explain complex ideas to both technical and non-technical stakeholders, and drive pragmatic, high-quality ML solutions that improve customer outcomes.