Senior Applied Data Scientist

05 ago - Firenze
Experteer Italy

Experteer Overview

As a Senior Applied Data Scientist, you shape data-driven product solutions at team.blue, blending AI with practical business insight. You will own end-to-end data science and ML initiatives from problem framing to deployment, influencing key metrics and ROI. You’ll collaborate with cross-functional teams to translate complex analyses into actionable business impact, and you’ll stay at the forefront of DS/ML/AI developments. This role offers the chance to scale innovative models across a growing customer base and contribute to a mission-driven, inclusive culture.

Retribuzione / Benefits

- Decompose multi-domain business problems with ROI focus and plan suitable methods from POC to production
- Develop data science and ML solutions, including GenAI, to extract insights and drive value
- Own end-to-end ML/AI projects: feature engineering, modeling, evaluation, retraining, deployment
- Translate analytical results into actionable insights for stakeholders to improve business metrics
- Collaborate with cross-functional teams to deliver DS/ML/AI solutions




- Research latest DS/ML/AI developments and apply them to improve systems
- Document processes, code, and findings for knowledge sharing

Responsabilità

- 8+ years of hands-on industry experience solving data science and ML problems across multiple verticals
- Expert programming in Python and SQL with DS/ML frameworks (Scikit-learn, Pandas, PyTorch)
- Strong problem solving and ability to tackle under-specified problems with clarity
- Deep understanding of statistical and ML methods from SVMs to deep learning and LLMs
- Experience owning ML/AI projects end-to-end from conception to containerization
- Proven track record of models in production with measurable business impact
- Experience applying statistics (regressions, A/B testing, clustering, probability) to business problems
- Strong communication skills and ability to present analyses persuasively
- Ability to collaborate effectively with cross-functional teams

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