Engineering Manager, Data & Machine Learning
New
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OverstoryMachine Learning, Climate Tech
United States, the Netherlands, United Kingdom, Ireland, Estonia, Portugal, France, Sweden, Switzerland, Denmark and Canada, Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)Full-TimeManager
Salary not disclosed
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Job Details
- Experience
- 8+ years of professional experience building ML- or data-driven systems, at least 3 years’ experience leading and managing ML or data-focused teams
- Required Skills
- PythonMachine LearningProduct ManagementData scienceSoftware Engineering
Requirements
- 8+ years of professional experience building ML- or data-driven systems.
- 3+ years of experience leading and managing ML or data-focused teams.
- Technical depth in machine learning, data systems, or applied ML to guide technical decision-making.
- Proficiency in working with Python-based ML or data workflows.
- Experience working in a high-growth scale-up or startup environment.
- Product-minded approach with the ability to demonstrate business impact through technology.
- Strong leadership and coaching mindset for supporting diverse engineering levels.
- Excellent communication and cross-functional collaboration skills.
- Passion for climate action and environmental technology.
- Nice to have: Experience applying software engineering best practices to data and ML systems, such as testing, monitoring, and production deployment.
Responsibilities
- Enable machine learning and data teams to operate as highly productive, cross-functional units.
- Support teams working with satellite imagery and geospatial datasets, balancing experimentation and production.
- Grow the team by attracting and hiring high-quality Data and ML talent.
- Provide regular 1:1 coaching and feedback to support career growth and team well-being.
- Act as a strategic partner to Product Managers to align technical decisions with business goals.
- Ensure technical approaches support future product and modeling requirements.
- Evolve Data and ML practices to improve collaboration, delivery speed, and learning.
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