What You'll Do
Define how success is measured across strategic initiatives by working closely with project teams during early discovery phases. Turn high-level business goals into precise, trackable KPIs that align stakeholders and guide decision-making.
Establish baselines, set performance targets, and design evaluation methods that objectively assess value creation. Develop standardized approaches and reusable tools to streamline measurement across projects, reducing setup time and increasing consistency.
Lead client discussions to surface implicit expectations, clarify outcomes, and build shared understanding of what success looks like. Translate qualitative aspirations into quantifiable commitments, ensuring accountability on both sides.
Step in when complex analytical challenges arise—performing multi-touch attribution, predictive modeling, or advanced segmentation as needed. Work hands-on with data to uncover root causes, validate results, and distinguish correlation from causation.
After solution deployment, analyze performance to verify impact. Build evidence-based narratives that inform adjustments, guide next steps, and ensure every analysis leads to action. Avoid unnecessary complexity by keeping focus on business outcomes.
Develop and maintain analytical standards across the organization. Document methods, create templates, and mentor team members to strengthen overall capability. Identify patterns across projects and feed insights back into organizational knowledge to accelerate future work.
Requirements
- Proficiency with SQL, Python, or R for statistical analysis, and experience with BI platforms such as Looker, Tableau, or Power BI
- Strong grasp of statistical techniques including significance testing, regression, cohort analysis, and A/B testing
- Experience handling large, diverse datasets and integrating multiple data sources
- Skill in designing dashboards and monitoring systems that support ongoing evaluation
- Deep familiarity with customer-centric metrics: conversion rates, customer acquisition cost, lifetime value, churn, and NPS
- Ability to connect operational performance to financial outcomes
- Proven capacity to convert vague objectives into specific, measurable indicators
- Scientific mindset—formulate hypotheses, test rigorously, and question assumptions
- Expertise in identifying biases, confounding factors, and misinterpretations in data
- Persistence in pursuing root causes, not just surface-level explanations
- Clear communication of insights tailored to audience—executive summaries for leadership, technical detail for analysts
- Experience facilitating difficult conversations around success criteria and managing misaligned expectations
- Self-directed work style with ability to manage multiple priorities based on impact
- Proactive identification of analytical needs before issues arise
- Comfort using AI tools to enhance analytical workflows
- Strong intellectual curiosity and commitment to continuous learning
- Native fluency in Italian and professional proficiency in English (B2 or higher)
Preferred Qualifications
- Prior experience in consulting, analytics, or data-intensive roles within fast-paced organizations
- Broad exposure across industries or domains to support pattern recognition and adaptability
- Familiarity with CRM systems and marketing technology stacks
Technical Stack
SQL, Python, R, Looker, Tableau, Power BI, AI-powered analytical tools
Work Environment
This role operates in a data-first culture where decisions are grounded in evidence, innovation is customized to client needs, and collaboration spans disciplines. The organization values rigor, proactive problem solving, and continuous improvement. Team members are expected to work independently, drive alignment, and contribute to collective knowledge.
