Aily Labs is a B2B SaaS company building an AI-powered decision intelligence app for enterprises. Our mobile-first platform combines company data with advanced machine learning, large language models and agentic AI to give business leaders clear, actionable insights in real time.
Instead of traditional dashboards and reports, Aily delivers simple, personalized recommendations that help teams decide and act faster across finance, supply chain, R&D, commercial, and more. The app is designed to be intuitive for end users and easy to integrate for IT, so companies can move from analysis and indecision to confident, data-driven decisions every day.
Founded in 2020 in Munich, Aily Labs has grown into a global team of 300+ people across Munich, Barcelona, Madrid, Cluj, and New York. Our mission is to democratize AI in business and enable leaders to Lead Boldly, turning complex data into decisions that drive real, measurable impact.
We are looking for Lead Data Scientists who are passionate about the power of AI and who thrive at the intersection of business, analytics, and AI: someone who not only trains models but also deeply understands the business context in which they're applied. Your job is to make sure AI is solving the right problems, using the right approaches, and driving measurable impact.
The Data Science Domains Department powers business-critical decision-making across four key areas of enterprise operations. We build and deploy AI-driven features that transform how business leaders understand and act on complex data challenges in their specific domains.
Each domain has distinct requirements, challenges, and opportunities—but all share the mission of delivering real-time, actionable AI insights that drive measurable business impact.
Finance (FIN): We enable smarter, faster financial decision-making across the enterprise by partnering with Finance teams to improve forecasting accuracy, planning agility, and financial transparency through AI-driven solutions. We tackle volatile revenue and demand signals, large-scale multi-dimensional forecasting, and resource allocation under uncertainty, while ensuring models remain explainable and actionable. Our work moves Finance beyond reactive reporting toward proactive data-driven decision-making, powered by production-grade ML systems at enterprise scale.
Manufacturing & Supply Chain (M&S): We optimize the end-to-end manufacturing and supply chain with cutting-edge AI. Our team works closely with supply chain champions across Fortune 500 companies to drive impact: from helping pharmaceutical companies to avoid out-of-stocks to reducing machine breakdown in consumer good factories. Our solutions consist of a mix of statistical, machine learning, GenAI, Knowledge Graph, and agentic techniques to tackle challenges such as low signal demand forecasting, explainability for supply chain autonomy, and providing detailed actionable recommendations based on a mix of textual, image, and structured data.
Research & Development (R&D): We are passionate about clinical operations and portfolio management. Our team partners closely with pharmaceutical and biotech companies to deliver innovative AI-driven solutions that optimize clinical trial recruitment and accelerate pipeline innovation. Some of the exciting use cases we’ve worked on include predicting patient enrollment, optimizing trial design, building knowledge graphs across the pharma ecosystem, and more.
Cross-Functional (XF): this team addresses critical business areas that extend beyond the scope of our other specialized domains. We apply AI to diverse functions spanning procurement, people analytics, commercial operations, and more - developing solutions that transform these essential but often underserved areas. By focusing on these complementary business functions, we ensure our AI platform delivers comprehensive value across the entire enterprise, helping organizations unlock insights and efficiencies in every corner of their operations.
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
Someone who thrives at the intersection of business, analytics, and AI and wants to ensure AI solves the right problems with measurable impact.
A scientist and builder: you explore multiple approaches, analyze results, and iterate fast, balancing cutting‑edge techniques with simple, scalable solutions.
A strong communicator who adapts the message to different audiences and enjoys working cross‑functionally with product, engineering, and business stakeholders.
Someone with a startup mindset: comfortable with ambiguity, proactive, and hands‑on when something needs fixing or improving.
Ready to Lead Boldly – helping business leaders make decisive decisions powered by real-time AI insights
Applicants must already have the legal right to work in Spain or Germany
Locations: Madrid (MAD), Barcelona (BCN) and Munich
Contract type: Permanent.
Work policy: hybrid (2 days per week in the office)
