- Design and implement end-to-end data pipelines (ingestion → transformation → quality → delivery) for multiple use cases with growing autonomy
- Build and maintain data infrastructure components (streaming pipelines, transformations, APIs, catalogs) using modern data tools
- Implement robust data quality frameworks, monitoring, and alerting systems at scale
- Optimize data workflows for cost, performance, e and reliability across multiple datasets
- Mentor junior team members on data engineering best practices and tooling
- Have comprehensive MLOps expertise, advanced Python/SQL skills, and domain specialization; enforce code quality standards across the team
- Own key features and projects; design and improve models, pipelines, and experimentation frameworks
- Communicate and align with internal/external stakeholders; turn business requirements into AI solutions; make speed vs. quality trade-offs
- Provide technical mentorship; set modeling standards and drive cross-functional delivery with PMs, engineers, and customers




- Have deep expertise in one technical area; lead by example on technical excellence, business acumen, and strategic vision
- Define and own AI domain roadmaps; transform ambiguous business challenges into structured action plans with clear milestones and dependencies
- Lead simultaneous projects across multiple workstreams; shape product strategy with PM/Eng; manage risks and ensure timely, high-quality releases
- Demonstrate strong business acumen: estimate AI solution impact on KPIs and business outcomes; identify domain-wide opportunities and influence strategy
- Provide leadership for the Data Science team: mentor and manage; define standards; drive impactful cross-functional delivery; empower team members

Benefits
- Fast growth path
- Hybrid working model
- General company and culture

Someone with a startup mindset: comfortable with ambiguity, proactive, and hands‑on when something needs fixing or improving xqbhyrx

Por favor, lea detenidame

📌 Lead Data Scientist (Madrid)
🏢 Aily Labs
📍 Madrid