Ancestry - Lehi, UT

posted 4 months ago

Full-time - Senior
Hybrid - Lehi, UT
Professional, Scientific, and Technical Services

About the position

AncestryDNA is seeking a motivated and talented Senior Machine Learning Scientist, Computational Genomics to join our ML science team. Our team is at the forefront of building computational and machine learning methods that connect people to the places and ancestors of their past through genomics. As a Senior ML Scientist, you will work with our enthusiastic world-class team of ML scientists, data scientists, and engineers to mine large datasets to understand populations, their histories, and their DNA sharing patterns. You will design, implement, and test novel algorithmic breakthroughs that will enrich our customers' lives. In this role, you will build new algorithms to solve complex problems to drive innovation. You will work collaboratively with our world-class team of ML scientists, data scientists, population geneticists, and engineers. Your responsibilities will include mining large datasets and running analyses to understand populations, their histories, and their DNA sharing patterns. This position is crucial for advancing our understanding of genomics and enhancing the services we provide to our customers. The ideal candidate will have a strong background in machine learning and computational biology, with a focus on applying these skills to real-world problems. You will be expected to contribute to the development of new methodologies and to collaborate effectively with a diverse team of professionals. Your work will directly impact the way we connect individuals with their ancestral histories and will play a key role in the ongoing innovation at Ancestry.

Responsibilities

  • Build new algorithms to solve complex problems to drive innovation.
  • Collaborate with a world-class team of ML scientists, data scientists, population geneticists, and engineers.
  • Mine large datasets and run analyses to understand populations, their histories, and their DNA sharing patterns.

Requirements

  • PhD or MS in computer science, machine learning, computational biology, statistics, or a related field with an emphasis in machine learning.
  • Minimum 2+ years of experience working in applied ML research outside of PhD.
  • Extensive experience developing and applying machine learning methods to decipher complex datasets.
  • Proficiency in Python and Linux/Bash.
  • Experience working with supervised, semi-supervised and unsupervised learning.
  • Extensive experience using ML frameworks such as Sklearn, Keras, Pytorch or Tensorflow.
  • Excellent verbal and written communication skills.
  • Creative thinking to develop novel approaches to complex problems.
  • Experience in working with large graphs.
  • Experience working in a cloud-based environment with big-data tools such as Spark/Hadoop (e.g. tens of billions of records).
  • Experience or expertise with genetics, population genetics, population geography, or demography.
  • Strong organizational and interpersonal skills.

Nice-to-haves

  • Experience in population genetics or demography.
  • Familiarity with big data processing tools and techniques.

Benefits

  • Health insurance
  • Dental insurance
  • Vision insurance
  • Eligibility for bonus
  • Equity options
  • Comprehensive benefits package
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