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# SENIOR DATA SCIENTIST*

- **Company:** The New Yorker
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Code Review, Continuous Integration, Corona (Software Development Kit), Apache Hadoop, Python (Programming Language), Machine Learning, Pair Programming, Software Engineering, SQL Databases, Pytorch, Apache Spark, Jupyter, Pandas, Pyspark, Scikit Learn, Information Technology, Machine Learning Operations, Software Version Control
- **Published:** June 20, 2026
- **Apply:** https://arc.dev/remote-jobs/j/new-yorker-senior-data-scientist-oyaze2qn4y

## About the Role

* University degree in a relevant field, e.g. computer science, statistics or physics with 3+ years of experience working as a Data Scientist
 * Strong software engineering skills (Python, SQL, CI/CD, testing, version control)
 * Extensive experience in the use of open-source data libraries like scikit-learn, pytorch, pyspark, jupyter, pandas and airflow
 * Experience with Spark, Hadoop or SQL as well as the application of modern software development methods
 * Experience deploying ML models to production
 * Excellent communication skills and stakeholder management
 * Passion for mentoring and raising the bar for the team
 * Good spoken and written German, fluent English is a must-have

## Description

* Combine curiosity, fast understanding of business processes, and strong analytical skills to identify and implement impactful Data Science solutions
 * Lead end-to-end development and operationalization of Machine Learning models within a team of experienced Data Scientists and Data Engineers
 * Actively manage stakeholders by translating business requirements into technical specifications and regularly presenting results
 * Write high-quality, maintainable code and mentor junior team members through code reviews and pair-programming
 * Continuously improve our internal tooling, shared libraries, and development practices
 * Apply industry best practices, including solid testing, documentation, and ensuring full reproducibility of work


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