The posting
Title: Data Scientist, Delivery
Location: Turin, Italy (hybrid)
Reporting to: CTO
Before you apply: Nebuly is where the bar is high and the vision is bold. We move fast, think deeply, and push each other to build the future of AI products. If you're ready to give your best, we'd love to hear from you.
ABOUT NEBULY
Nebuly is a fast-growing, VC-backed startup building the platform that proves the ROI of enterprise AI.
Every enterprise function (sales, customer support, HR, finance) is deploying AI agents at scale, and budgets are following fast. But most companies can't answer a basic question: is this spend actually working? The signal that could answer it is already there, in the millions of conversations happening every day between employees, customers, and these agents. It's unstructured, high-volume, and invisible without the right infrastructure.
Nebuly makes that signal visible. It sits on top of any enterprise AI deployment, turns those conversations into a clear answer on whether AI is working and where, and connects the dots back to ROI. Think of it as the accountability layer for enterprise AI: connect once, see the impact, prove the value, with no data ever leaving your environment.
Our customers include Oura, CNH Industrial, Vodafone, and Moncler. Demand is accelerating fast, and we're building the team to match.
THE ROLE
Every new customer brings a different AI deployment, different users, and different questions they need answered. Most of them start with a Proof of Value (PoV) or Proof of Concept (PoC): a few intense weeks in which we have to show, on their own data, that Nebuly delivers insights they can't get anywhere else. Plugging in the product is only half the job: the other half is making sure that what Nebuly shows is exactly what that customer needs to see. As a Data Scientist in our Delivery team, you own that second half, and you are the person who makes a PoV/PoC succeed.
You dive into each customer's data, find the trends that matter, and decide what is real signal and what is noise. You judge whether a metric, a topic, or an insight is actually useful for that specific customer, and you shape the product configuration accordingly. Throughout the PoV/PoC and the installation you work side by side with our revenue team and directly with the customer's own stakeholders: you agree on success criteria, you show them what their data is telling them, and you iterate until the product fits their needs perfectly and the value is clear enough to turn the pilot into a long-term deal.
You sit at the intersection of data, product, and customers: you turn raw conversational data into insights a business leader can act on, and you bring back to product and engineering what you learn in the field.
EXAMPLES OF YOUR DAILY RESPONSIBILITIES
- Work hands-on with customers during PoV/PoC phases: help define success criteria with them and the revenue team, and own the analytical side of the pilot from kickoff to final readout.
- Explore and analyse customer data during PoVs/PoCs and onboarding: write queries, slice the data, and identify the trends, patterns, and anomalies that matter.
- Assess whether a given data point, metric, or insight is relevant and valuable for the customer, and discard what isn't.
- Configure and fine-tune the product for each customer (topics, metrics, segments, dashboards) so that it answers their real business questions.
- Work closely with the revenue team before and during installation to understand customer goals and translate them into an analytics setup.
- Run regular sessions with customers' stakeholders during the PoV/PoC to present findings, validate hypotheses, and iterate on the configuration together.
- Prepare the final PoV/PoC readout with the revenue team: the insights uncovered, the value demonstrated, and the case for moving to production.
- Build Python scripts and notebooks to automate recurring analyses, data quality checks, and onboarding steps.
- Evaluate the quality of the insights our AI pipelines produce on customer data, and flag issues to the AI and engineering teams with clear evidence.
- Turn what works into repeatable playbooks, so that every new installation is faster and better than the last.
- Bring patterns you see across customers back to product and engineering to help shape the roadmap.
WHAT WE LOOK FOR
- 2 to 5 years of experience as a Data Scientist, Data Analyst, Analytics Engineer, or in a similar analytics role.
- Strong SQL. You write complex queries comfortably (joins, window functions, aggregations) and you know how to get answers out of a database efficiently.
- Strong Python. You are fluent with the data stack (pandas or polars, notebooks, plotting libraries) and you write clean, reusable code, not just one-off scripts.
- An analytics mindset. You know how to go from a vague business question to a precise analysis, and you can tell a meaningful trend from a statistical artefact.
- Business sense. You care about what the customer will do with an insight, not only about how elegant the analysis is.
- Customer-facing and comfortable in pilots. You can present data to both technical and non-technical stakeholders, you are comfortable working directly with customers during PoV/PoC phases, and you can keep a pilot on track under time pressure.
- Hands-on with AI agents. You already use tools like Claude, Claude Code, Cursor, or similar to move faster in your analyses, and you know how to verify what they tell you.
- Strong ownership: you follow a customer installation through until the product is delivering value.
- Excellent written and spoken English.
NICE TO HAVE
- Experience in a customer-facing analytics, consulting, or solutions role, ideally running PoVs, PoCs, or pilots with enterprise B2B customers.
- Experience with analytical databases such as ClickHouse, BigQuery, or Snowflake.
- Experience working with unstructured or text data, NLP, or LLMs.
- Experience with BI and dashboarding tools.
- Italian language skills.
WHAT WE OFFER
High-impact work in small, fast-moving teams. At Nebuly, you'll work in small, entrepreneurial teams with a high degree of ownership and autonomy. Regardless of your seniority, your work has a direct impact: every PoV/PoC you run is a customer deciding whether to bet on our platform, and every installation you deliver is a customer who sees real value from day one.
A platform for real growth. As more companies rely on our platform to understand and optimize their AI experiences, new challenges emerge constantly. You'll work with some of the largest enterprises in Europe and the US, you'll see how AI is actually used across very different organisations, and you'll have clear paths to grow into senior data science, solutions, or customer-facing leadership roles.
Competitive pay + equity. We offer a competitive salary depending on experience, plus meaningful stock options in a fast-scaling company.
