Data Science Lead - Hybrid ML Strategy & Delivery

team.blue

Firenze

Ibrido

EUR 90.000 - 130.000

Tempo pieno

41 ore fa

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Descrizione del lavoro

team.blue seeks an experienced Senior Data Scientist Lead to guide the Data & Analytics team while remaining hands-on with the most complex projects. You will shape data-driven strategy, mentor two data scientists, and collaborate with product, engineering, and business leaders to deliver value through ML, predictive modeling, and rigorous analyses.

You will drive the data science roadmap, translate business needs into analytics initiatives, and ensure delivery quality across the team.

Competenze

Degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
5+ years of experience in data science, including at least 3 years in a data science lead, team lead or equivalent leadership position, with a proven track record of solving complex business problems using data.
Proven Leadership Experience: Demonstrable experience line-managing and developing data scientists. You can point to concrete examples of people you have hired, coached or grown, and of teams you have led through delivery.
Hands-on Credibility: You are still actively building — comfortable writing production-quality code, reviewing your team’s work, and being the person others come to when a problem is genuinely hard.
Stakeholder Management: Experience representing a data science team to senior stakeholders: setting expectations, saying no when needed, and defending the team’s priorities.
Strong understanding of business operations and the ability to align data science projects with business objectives.
Communication Skills: Ability to translate technical insights into business recommendations and communicate with stakeholders at all levels.
Problem-solving: Strong analytical thinking with the ability to handle complex and unstructured data.

Mansioni

Team Leadership & Development: Lead, coach and grow a team of two data scientists — setting objectives, holding regular one-to-ones, giving feedback, and actively supporting their technical and career development.
Hands-on Delivery: Stay personally involved in delivery, owning the most complex or business-critical projects end to end and setting the technical standard for the team through code reviews and pairing.
Planning & Prioritisation: Manage the team’s backlog and capacity, balance competing stakeholder requests, and make sure work is delivered at a predictable pace and quality.
Business Insight Development: Understand the key business challenges and opportunities, and use data to develop solutions that align with strategic objectives.
Data Strategy: Own the data science roadmap together with leadership, defining priorities based on business needs and opportunities, and translating them into a concrete plan for your team.
Predictive Modeling & Machine Learning: Build, deploy, and maintain machine learning models to forecast trends, optimize processes, and drive business outcomes.
Data Analysis & Visualization: Analyze large, complex datasets to extract actionable insights, and present findings to both technical and non-technical stakeholders.
Data science pipeline: Advise, build and continuously improve the data science pipeline which best responds to team.blue analytics needs.
Cross-functional Collaboration: Work closely with business leaders, product teams, and engineers to ensure that data solutions meet business requirements.
Continuous Improvement: Stay up to date with the latest trends in data science, AI, and machine learning to continuously improve the team’s capabilities.