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# Data Scientist

- **Company:** Indigo Slate
- **Location:** Madrid, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Computer Programming, Distributed Systems, Python (Programming Language), Machine Learning, NumPy, Pattern Recognition, SQL Databases, Pandas, Pyspark, Scikit Learn, Data Analytics, Machine Learning Operations
- **Published:** July 21, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/p61n0ozm5p

## About the Role

* 3-5 years of experience in Machine Learning.
 * Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL.
 * Hands-on experience with Machine Learning techniques, including regression, classification, and time series analysis.
 * Experience with AWS and cloud technologies.
 * Knowledge of MLflow for model lifecycle management.
 * Strong analytical and mathematical mindset.
 * Proactive, collaborative, and data-driven approach.

Nice to Have

 * Experience with PySpark.
 * Knowledge of AWS or Azure cloud platforms.
 * Experience with Git and version control best practices.
 * Familiarity with MLOps practices and MLflow.

## Description

* Transform data into insights to identify & quantify business opportunities. Solve business problems by employing machine learning, artificial intelligence, statistical learning, pattern recognition, or high-performance computing techniques.
 * Design, develop, validate, and optimize machine learning models and advanced analytical algorithms to solve complex business problems.
 * Develop scalable and efficient data science solutions capable of processing large volumes of data in high-performance or distributed computing environments.
 * Apply strong programming skills to implement optimized algorithms and reusable analytical components.
 * Manipulate and analyze complex, high-volume, high-dimensionality data from varying sources using a variety of tools and data analysis techniques.
 * Communicate and translate complicated results & their implications to business stakeholders.
 * Actively participate to a community of practice for data scientists.


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