Role Overview
We are seeking an experienced
Engineering Manager - Data Science to lead a high-performing Data Science squad responsible for delivering scalable machine learning solutions, predictive models, and AI-driven products that drive business impact.
The ideal candidate combines deep technical expertise in Data Science and Machine Learning with strong people leadership capabilities. This role requires a strategic thinker who can manage a multidisciplinary squad, define technical roadmaps, mentor engineers and data scientists, and collaborate closely with Product, Engineering, Analytics, and Business stakeholders.
Key Responsibilities
Leadership & Team Management
- Lead, coach, and develop a squad of Data Scientists, Machine Learning Engineers
- Drive team performance through goal setting, mentoring, career development, and continuous feedback
- Build and foster a culture of innovation, ownership, collaboration, and technical excellence
- Support recruitment, onboarding, and talent development initiatives
- Manage squad capacity, planning, and execution to ensure successful delivery of strategic projects
Technical Leadership
- Define and execute the Data Science roadmap aligned with business objectives
- Lead the design, development, deployment, and monitoring of machine learning models and AI solutions
- Establish engineering best practices for model development, experimentation, MLOps, and production deployment
- Guide architectural decisions related to data platforms, machine learning infrastructure, and AI systems
- Ensure scalability, reliability, and maintainability of Data Science solutions
Stakeholder Management
- Partner with Product Managers, Engineering Leaders, and Business stakeholders to identify opportunities for data-driven decision making
- Translate complex business problems into analytical and machine learning solutions
- Communicate technical findings and recommendations to both technical and non-technical audiences
- Drive alignment across cross-functional teams to deliver measurable business outcomes
Delivery & Execution
- Oversee end-to-end project delivery from discovery and experimentation to production deployment
- Monitor KPIs and model performance to ensure continuous improvement
- Balance technical debt, innovation, and business priorities effectively
- Drive agile delivery practices within the squad
Requirements
- 10+ years of experience in Data Science, Machine Learning, Software Engineering, or related technical fields
- 4+ years of people management experience leading Data Science or Machine Learning teams
- Proven experience leading cross-functional squads in product-driven environments
- Demonstrated track record of deploying machine learning models into production
Technical Skills
Strong expertise in:
- Machine Learning
- Statistical Modeling
- Predictive Analytics
- Deep Learning
- NLP and/or Generative AI
- Experiment Design and A/B Testing
Advanced proficiency in:
- Python
- SQL
- Data Visualization tools
Experience with:
- MLOps practices
- Model monitoring and governance
- Cloud platforms (Azure, AWS, or GCP)
- Data Engineering concepts and modern data platforms
Familiarity with:
- LLMs and Generative AI applications
- Feature stores
- Recommendation systems
- Real-time machine learning solutions
Preferred Qualifications
- Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field
- Experience within FinTech, Digital Products, E-commerce, Banking, or Technology organizations
- Experience managing large-scale data platforms and AI initiatives
- Knowledge of modern software engineering practices and DevOps methodologies
Benefits
- Lead cutting-edge AI and Data Science initiatives
- Build products impacting millions of users
- Work with highly talented engineering and product teams
- Shape the future of data-driven decision making within the organization.
- When you come to our b_labs office, you'll find creative workspaces and an open design to foster collaboration between teams.
- You know best whether you want to work from home or in the office.
- From Day 1 you will receive all the equipment you need be successful at work.
