Perform exploratory data analysis (EDA) to identify trends, insights, and opportunities.
Design, build, train, and evaluate machine learning, deep learning, and Generative AI models.
Define model evaluation frameworks, conduct A/B testing, and monitor model performance and drift.
Deploy data science solutions through APIs, batch pipelines, and cloud-based platforms.
Optimize model inference performance, scalability, latency, and cost.
Collaborate with data engineers, software engineers, product managers, and designers to integrate solutions into production systems.
Contribute to internal innovation initiatives, research projects, and thought leadership activities.
Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related discipline.
Strong programming skills in Python and SQL.




Hands-on experience with machine learning frameworks and the Python data science ecosystem.
Experience developing predictive, classification, optimization, and statistical models using structured and unstructured data.
Experience with model deployment, monitoring, testing, and productionization.
Experience with big data technologies such as PySpark, Hadoop, Hive, or similar frameworks.
Familiarity with Databricks, Airflow, Kedro, Dask, RAPIDS, or comparable data engineering tools.
Knowledge of cloud platforms including AWS, Azure, or GCP.
Experience with containerization and orchestration tools such as Docker and Kubernetes.
Exposure to software engineering best practices and MLOps.
Consulting or client-facing project experience is highly desirable.
Skills: pyspark,sql,python
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📌 Data Marketing Scientist (Madrid)
🏢 Virtual Connect Solutions
📍 Madrid