Principle Data Scientist; mfd

The Data Science team partners with groups across the company and leverages state-of-the-art technology to offer solutions that set Auto Scout
24 apart. In this role you'll collaborate cross-functionally with product engineering and business teams to design, build and scale AI solutions that set us apart in the industry. You'll bring deep technical expertise, a passion for innovation and a strong product mindset to develop ML products that solve real-world problems and deliver measurable business value.

Our ideal candidate is an experienced data science leader who thrives in a dynamic fast-paced environment that combines the stability of an industry leader with the agility of a startup culture. You are curious, proactive and committed to continuous learning especially in emerging areas like Generative AI and Large Language Models (LLMs).

You should be comfortable engaging with all levels of the organization from peers to executives and possess the ability to distill complex information into clear actionable strategies that drive business decisions and create value.

At Auto Scout
24 we appreciate different lifestyles and cultural backgrounds. We welcome diversity as a strength. Our organization is made up of more than 50 different nationalities working together inclusively and respectfully.

The role is Hybrid (2 days a week office attendance).

• Shape the strategic direction and vision of Data Science across the organization by identifying transformative AI/ML opportunities and championing the team’s evolving role in a rapidly advancing GenAI landscape.
• Lead the design and deployment of predictive and generative AI models that power personalization, pricing, search and optimization in marketplace and fintech domains.
• Collaborate with product leaders to align ML initiatives with strategic business goals and drive product innovation through data-driven experimentation and modeling.
• Architect scalable ML infrastructure and automated workflows using cloud-native tools (e.g. AWS EC2, Kubernetes) to support efficient model training, deployment and analytics across diverse datasets.
• Ensure long-term performance and compliance of production AI models through robust governance and monitoring.
• Provide technical leadership and mentorship to data scientists, shaping an innovative team culture and fostering high performance and continuous learning.
• Serve as a cross‑functional technical leader shaping company-wide technical initiatives beyond data science. Partner with engineering, product and platform teams to influence architecture innovation agendas and technical standards across the organization.
• Act as a senior technical advisor leading resolution of complex modeling issues and acting as the escalation point for critical incidents.
• Lead the exploration and strategic application of GenAI, identifying high‑impact use cases and guiding their integration across products and platforms.

• Advanced academic credentials in a quantitative field such as Computer Science, Engineering, Mathematics or related discipline.
• 10 years of experience in data science, machine learning or applied AI with a strong portfolio of high‑impact projects in production.
• Expert‑level programming skills in Python and SQL and fluency with leading ML/AI frameworks (e.g. scikit‑learn, Tensor Flow, PyTorch).
• Direct experience with GenAI/LLM technologies including tools like Hugging Face, Lang Chain, OpenAI APIs, vector databases and fine‑tuning methods.
• Deep knowledge of machine learning algorithms (supervised, unsupervised, deep learning), including model evaluation, explainability and selection for business‑critical use cases.
• Strong hands‑on experience with cloud infrastructure (AWS), containerization (Docker) and orchestration (Jenkins, Airflow).
• Proven capability in MLOps, including CI/CD pipelines, model monitoring, versioning and automated retraining.
• Experience deploying and serving models through APIs (e.g. Flask, FastAPI) in both real‑time and batch‑processing environments.
• Excellent communication and stakeholder management skills, able to translate complex concepts into actionable insights for non‑technical…