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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data analysis and customer insights, leveraging strong SQL and Python skills to drive actionable outcomes. Proficient in presenting findings to diverse stakeholders and managing customer-facing analytics projects effectively.
Highest-signal resume keywords
Strong SQL SkillsPython ProgrammingCustomer-Facing Analytics ExperienceExperience with Analytical DatabasesExcellent English Communication
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
SQLPythonData AnalysisStatistical AnalysisData VisualizationNLPLLMsData Quality ChecksMetrics ConfigurationDashboarding
Soft Skills
Business SenseStakeholder PresentationOwnershipTime ManagementCollaboration
Tools & Technologies
ClickHouseBigQuerySnowflakeBI ToolsAI-Agent Tools
Industry Keywords
Proof of ValueProof of ConceptEnterprise B2BCustomer InsightsAnalytics Engineering
Tech Stack
Tools & technologiesBigQueryPandasPythonSQL
About the role
Key responsibilities & impact- Own the analytical side of customer Proof of Value and Proof of Concept pilots from kickoff to final readout
- Define success criteria with customers and the revenue team
- Explore and analyse customer data during PoVs/PoCs and onboarding
- Write queries, slice data, and identify relevant trends, patterns, and anomalies
- Assess the relevance and value of metrics, data points, and insights for each customer
- Configure and fine-tune product topics, metrics, segments, and dashboards
- Work with the revenue team to understand customer goals and translate them into analytics setups
- Run sessions with customer stakeholders to present findings, validate hypotheses, and iterate on configuration
- Prepare final PoV/PoC readouts covering insights, demonstrated value, and the case for production adoption
- Build Python scripts and notebooks for recurring analyses, data quality checks, and onboarding automation
- Evaluate AI pipeline insight quality on customer data and flag issues to AI and engineering teams
- Create repeatable installation playbooks
- Bring cross-customer patterns to product and engineering to help shape the roadmap
Requirements
What you’ll need- 2 to 5 years of experience as a Data Scientist, Data Analyst, Analytics Engineer, or in a similar analytics role
- Strong SQL, including joins, window functions, aggregations, and efficient database querying
- Strong Python, including pandas or polars, notebooks, plotting libraries, and clean reusable code
- Ability to turn vague business questions into precise analyses and distinguish meaningful trends from statistical artefacts
- Business sense and focus on actionable customer insights
- Ability to present data to technical and non-technical stakeholders
- Comfortable working directly with customers during PoV/PoC phases and keeping pilots on track under time pressure
- Hands-on experience with AI-agent tools such as Claude, Claude Code, Cursor, or similar
- Ability to verify AI-generated outputs
- Strong ownership of customer installations through value delivery
- Excellent written and spoken English
- Experience with customer-facing analytics, consulting, or solutions roles, ideally involving enterprise B2B PoVs, PoCs, or pilots
- Experience with analytical databases such as ClickHouse, BigQuery, or Snowflake
- Experience with unstructured or text data, NLP, or LLMs
- Experience with BI and dashboarding tools
- Italian language skills
Benefits
Comp & perks- Competitive salary depending on experience
- Meaningful stock options in a fast-scaling company
- High degree of ownership and autonomy
- Clear paths to grow into senior data science, solutions, or customer-facing leadership roles
- Opportunity to work with some of the largest enterprises in Europe and the US
- Work in small, entrepreneurial, fast-moving teams