Data Scientist, Data Platform Sciences

Data Scientist, Data Platform Sciences

This job is no longer open

We are seeking a talented and experienced Data Scientist to join our team and contribute to the enhancement and upleveling of our machine learning platform. If you're passionate about improving the lives of machine learning engineers and scaling our company's ML capabilities, as well as staying at the forefront of advancements in the field, then we encourage you to apply. Join our team and help us revolutionize the way we train, test, tune, manage, and deploy advanced ML models, while collaborating with a diverse and highly skilled team of data scientists and engineers who are dedicated to pushing the boundaries of ML innovation. The coding skills you bring to the table will give you the opportunity to mentor and guide other data scientists, fostering a culture of continuous learning and growth within the team.

 

What you’ll do:

  • Collaborate with machine learning engineers to identify pain points and challenges in the development and deployment of ML models.
  • Research and implement innovative solutions to optimize the efficiency, scalability, and reliability of the machine learning platform.
  • Analyze and evaluate the performance of existing machine learning models, identifying areas for improvement and optimization.
  • Collaborate with cross-functional teams to gather requirements, align on project goals, and drive the implementation of new features and enhancements to the machine learning platform.
  • Leverage our extensive and valuable metadata set to generate innovative suggestions and strategies, identifying efficient shortcuts to evaluate hypotheses and assess the potential of ideas.

What we’re looking for:

  • 2+ years of hands-on experience working as a data scientist, applied scientist, software engineer or ML engineer.
  • Proven ability to design and implement machine learning models, as well as evaluate and optimize their performance on large datasets.
  • The ability to write clean, efficient, and scalable code that can be easily maintained and extended by other team members.
  • Proficiency in software development best practices, including version control systems such as Git, to ensure efficient collaboration, code management, and reproducibility in a data science environment.
  • Familiarity with workflow management tools such as Apache Airflow to create and schedule data pipelines, allowing for automated and reliable execution of machine learning workflows.
  • Enthusiasm and desire to work collaboratively in a team that is dedicated to enhancing the machine learning infrastructure and implementing best practices for model development, deployment, monitoring, and scalability.

 

This position is not eligible for relocation assistance.

 

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This job is no longer open
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