Data Scientist Team Lead

28 set - Firenze
Team.Blue

As Data Science you will steer a small team while remaining hands-on in delivery, translating complex data into business value. You will shape the data science roadmap and prioritize initiatives that support strategic objectives across cross-functional partners. Your work will influence decision-making and drive operational improvements through machine learning, predictive modeling, and analytics. This role blends leadership with hands-on coding to maintain high technical standards and measurable impact.Lead and develop a two-person data science team with clear objectives and ongoing coachingOwn the most complex, business-critical projects end-to-end and set technical standards via reviews and pairingPlan and prioritize the team's backlog and ensure predictable delivery with qualityTranslate business challenges into data-driven solutions aligned with strategic goalsOwn the data science roadmap with leadership and translate priorities into concrete plansBuild, deploy,



and maintain ML models to forecast trends and improve processesAnalyze large datasets and present actionable insights to both technical and non-technical stakeholdersAdvise and improve the data science pipeline to meet analytics needsCollaborate with business, product, and engineering stakeholders to ensure data solutions meet requirementsStay current with trends in data science, AI, and ML to enhance capabilitiesDegree in Data Science, Statistics, Mathematics, Computer Science, or related field5+ years in data science with at least 3 years in lead/management rolesProven line management and development of data scientistsHands-on credibility with production-quality coding, code reviews, and xysqume troubleshootingStakeholder management at senior levels, ability to set expectations and defend prioritiesStrong understanding of business operations and ability to align data projects with objectivesExcellent communication skills to translate insights for diverse audiencesProblem-solving skills with proficiency in handling complex/unstructured dataleadership and people developmentclear communicationPython, R, or ScalaML frameworks: TensorFlow, Scikit-learnSQL and handling large datasets#J-18808-Ljbffr

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