Research Data Scientist - Machine Learning

Our story is the one of a group of Cloud and technology enthusiasts who always had a clear goal : make things much easier for tech companies. Since no one was really stepping up to fill that gap in Spain’s Cloud sector, we figured—why not build our own product?

Today, Jotelulu’s products are used in thousands of offices and businesses in retail, construction, industry, hospitality, transportation, and more, across over 8 countries in Europe and the Americas.

Every step we take is driven by the desire to do things better, bring something new, and shake things up—because that’s the only way innovation truly has meaning.

Jotelulu powers products like Servers, Remote Desktop, DRaaS, File / Object Storage and our Marketplace—and we are moving fast towards a all-in-one platform for IT companies.

Your mission : Turn our rich operational and product telemetry into trustworthy, timely, secure, and business‑ready data. We’re hiring a Principal Data Scientist / Developer—part architect, part builder, part strategist—to own our end‑to‑end data foundation and accelerate impact from insights to shipped improvements. You’ll partner with Product and engineering leads to design the next‑gen data platform (batch and streaming), define our metrics and contracts, and ship models (analytics, ML, and LLM‑assisted) that lift activation, expansion, and reliability. Reporting to the COO, you’ll work hands‑on while coaching others, translating business questions into robust, production‑grade data products. This role is based in Madrid, Spain, with an hybrid work fashion.

This isn’t about dashboards alone—it’s about building the engines that move the business.

Responsibilities

End-to-end data infrastructure.

Data quality, integrity, and availability.

CI / CD for data, contracts, tests, and observability as first‑class citizens.

Design / optimize ingestion, transformation, and analysis workflows for structured and unstructured data.

Own core metrics, semantic layers, reporting models, and feature stores aligned to the partner funnel (SQL→MQL→SQL→ARR).

Implement / improve dashboards (Dash / Plotly, Power BI, Tableau, Looker).

Data modeling (dimensional, lakehouse, feature stores).

Data quality & observability (detect / fix inconsistencies).

Automate extraction / transformations, data testing, and deployment.

Linux, bash, Git, containerization; SQL / NoSQL; Flask / FastAPI for APIs; data stack : Pandas, scikit‑learn, Polars, DuckDB; PyTorch, HuggingFace, TensorFlow; Dash  /  Plotly  /  Power BI; Slack; Microsoft O365; Jira; Confluence; cloud platforms & data services.

It will be a perfect match if… You spot data gaps early and propose scalable solutions without waiting for direction.

You turn analysis into compelling narratives that move execs and engineers to act.

You design data models and APIs that make cloud workflows intuitive for partners and internal teams.

You can lead the full data lifecycle.

You translate questions into analysis, and insights into shipped changes.

You champion data integrity and responsible AI to improve real outcomes.

8+ years across Data Science / Analytics / Engineering (including leading initiatives), with shipped data products and measurable business impact.

Mastery of data tooling. Python (preferred) and / R; SQL & NoSQL; visualization (Power BI, Tableau, Looker, Dash  /  Plotly); cloud data services. You use AI responsibly to speed up quality work.

Skillset

English skills.

Data

SQL & NoSQL excellence.

Schema design, performance tuning, partitioning, indexing.

ETL / ELT & orchestration.

Reliable pipelines (batch / stream) with monitoring, alerting, and recovery.

From baseline models to rigorous A  /  B tests and causal inference on structured / unstructured data.

Power BI, Tableau, Looker, and Dash  /  Plotly for decision‑ready views.

Data tests, lineage, contracts, catalogs, and CI / CD for data.

Quality by design. Build / consume services with Flask / FastAPI; productionize models and data apps.

Cloud & data services.

Practical fluency with cloud storage / compute and managed data offerings.

Python, Pandas, Polars, DuckDB, scikit‑learn; DL with PyTorch / TensorFlow / HuggingFace.

Linux, bash, Git, containerization; automation, testing, and CI  /  CD for code and data.

Data Analytics team compliance The Data Analytics team ensures secure and responsible data use in line with ISO 27001, ENS, and HDS—protecting confidentiality, integrity, and availability. We anonymize and encrypt where applicable, enforce access controls, uphold data quality, and ensure that analysis tools / platforms are compliant.

Remote work model Hybrid remote model (50‑50 per year). 2 days at home, 3 in the office. Summer and Christmas full remote.

Holidays

• . Flexible starting hour every day, and working half day on Fridays. Julio / agosto intensivo

Training budget.

You’ll have €500 per year to invest in your professional development.

Private Medical Insurance.

With a budget for all the days you come to de office.

As a Principal Data Scientist / Developer, you’ll have opportunities to take on larger cross‑company responsibilities, with a potential chance of getting access to our stock unit program.

A beautiful office overlooking Plaza España, right in the heart of Madrid and well connected to the entire city.

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