Python Developer - Data & Analytics
Role details
Job location
Tech stack
Job description
- Data ingestion & ETL: Build robust Python-based pipelines to collect, clean, validate, and join large datasets from multiple sources (APIs, logs, databases, files).
- Data quality & troubleshooting: Detect, investigate, and resolve data discrepancies and integrity issues; implement automated validation and monitoring.
- Data analysis & reporting: Analyze datasets to uncover trends and actionable insights; produce repeatable reports and dashboards for stakeholders.
- Dashboards & visualizations: Develop and maintain dashboards (Tableau, Power BI, or equivalent) and programmatic visualizations for product and business teams.
- Collaboration: Work closely with product and engineering to translate business requirements into data solutions, instrumentation, and KPIs.
- Predictive modeling & ML: Design, train, evaluate, and deploy statistical models and machine learning solutions (scikit-learn, PyTorch, TensorFlow, etc.) to forecast trends and support decision-making.
- Performance & scalability: Optimize queries and data workflows (SQL, ClickHouse, MongoDB) for low-latency and high-throughput environments.
- Prototyping & research: Rapidly prototype algorithms and analyses in Python (or MATLAB when needed) and turn prototypes into production-ready code.
Requirements
Do you have a Bachelor's degree?, * Bachelor's degree in Computer Science, Mathematics, Statistics, Telecommunications, or related field (advanced degree a plus).
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At least 3 years of work experience.
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Strong production experience developing in Python (data engineering, analysis, and/or ML).
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Proficient with SQL and experience with ClickHouse and MongoDB (or similar).
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Experience collecting, analyzing, and reporting data from lab and production systems.
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Experience with BI tools (Tableau, Power BI, or similar).
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Familiarity with data mining and machine learning algorithms and libraries (scikit-learn, pandas, NumPy).
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Experience prototyping algorithms in Python (MATLAB experience a plus).
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Soft Skills.
- Analytical Capabilities, Critical thinking, Problem solving, Eager to learn, and Proactive.
- Planning and Organizational skills, Active listening, Communication skills.
- Teamwork, autonomous.
- Customer and results orientation.
- Fluency in both English and Spanish
- Ability to work in hybrid in Madrid.
Nice-to-Have:
- Knowledge of statistical signal processing or communication systems.
- Experience with Wi-Fi or networking technologies.
- Experience deploying ML models and building monitoring for model performance.
- Familiarity with cloud data platforms and orchestration tools (Airflow, Kubernetes, AWS/GCP/Azure).