Dein persönlicher KI-Karriere-Agent
Leading ML, forecasting, and recommendation solutions development on Databricks. 5+ years delivering ML solutions from discovery to deployment required. Four-day Flexi-Week, hybrid/remote work.
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Anforderungen
- 5+ years of experience as Data Scientist, ML Engineer, or similar
- Delivering ML and analytical solutions from discovery to deployment
- Advanced Python proficiency with data science libraries
- Strong Databricks experience (Jobs, Asset Bundles, Delta Lake, MLflow)
- Working with business stakeholders to define and scope solutions
- Mentoring data scientists or technical leadership
- Bachelor's degree or higher in quantitative discipline
- Strong statistical, analytical, and problem-solving skills
- Expertise in ML and predictive modeling in production
- Ability to evaluate and refine models
- Strong stakeholder management and communication skills
- Ability to operate independently and navigate ambiguity
- Experience mentoring and supporting data scientists
- Collaborative mindset and cross-functional teamwork
Aufgaben
- Lead development and deployment of machine learning, forecasting, recommendation, and analytical solutions
- Partner with stakeholders to identify opportunities and translate business challenges into data-driven solutions
- Design and implement robust evaluation frameworks, experiments, and success metrics
- Apply statistical modelling, machine learning, and advanced analytical techniques
- Build scalable feature engineering, model development, and deployment workflows
- Drive rapid MVP development and validate ideas
- Define and promote best practices for model development, evaluation, monitoring, and governance
- Mentor and support other data scientists
- Communicate findings, recommendations, and technical concepts clearly
- Contribute to the evolution of the Data Science roadmap
Berufserfahrung
Ausbildung
Sprachen
Tools & Technologien
Benefits
- Four-day Flexi-Week
- Hybrid/remote working scheme
- Full pay
- Monthly work expense contribution
- Remote working furniture package
- Health and wellbeing initiatives
- Sports offers
- Extensive training suite
- Peer-to-peer recognition programme
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