Data Science Engineering Team Lead

3 weeks ago


Dinan, Bretagne, United States Hispanic Technology Executive Council Full time
Job Description:

The Data Science Engineering Team Lead position at Hispanic Technology Executive Council is a critical role that oversees the development and implementation of machine learning applications. This individual will lead an Agile team dedicated to productionizing machine learning applications and systems at scale, ensuring high availability and performance.

This leadership position requires strong technical expertise in designing and building data-intensive solutions using distributed computing, as well as experience with industry-recognized machine learning frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow. The ideal candidate will have a proven track record of developing performant, resilient, and maintainable code, and will be experienced in leading teams developing ML solutions using industry best practices, patterns, and automation.

The successful Data Science Engineering Team Lead will have a deep understanding of machine learning modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation. They will leverage this knowledge to inform their decisions on ML infrastructure and develop strategies for efficient model deployment.

Key Responsibilities:
  • Lead an Agile team responsible for designing, building, and delivering machine learning applications and models.
  • Collaborate closely with Product and Data Science teams to ensure alignment and effective communication.
  • Develop and implement strategies for efficient model deployment and scalability.
  • Oversee the development of performant, resilient, and maintainable code.
  • Provide guidance on industry best practices, patterns, and automation for ML solution development.

Requirements:

  • Bachelor's degree in computer science, electrical engineering, mathematics, or a related field.
  • At least 6 years of experience designing and building data-intensive solutions using distributed computing.
  • Proven expertise in one or more industry-recognized machine learning frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow).
  • Strong leadership skills with experience leading teams developing ML solutions.
  • Excellent communication and collaboration skills.

Preferred Qualifications:

  • Master's or doctoral degree in a relevant field.
  • Experience with cloud-based architectures and technologies (AWS, Azure, Google Cloud Platform).
  • Industry impact through conference presentations, papers, blog posts, open source contributions, or patents.

Salary Estimate: $180,000 - $220,000 per year, depending on experience.



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