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Qualcomm IT Data Scientist in San Diego, California

Company:

Qualcomm Incorporated

Job Area:

Information Technology Group, Information Technology Group > IT Data Scientist

Responsibilities

  • Performance exploratory analysis and feature engineering on a large-scale data store

  • Develop and deploy machine learning and deep learning models to be able to perform predictive, descriptive, and inferential, analytics to identify trends and relationships

  • Define and conduct statistical hypothesis testing to ensure machine learning models reliability in production

  • Create data visualizations to present derived insights and build out operational visualizations to measure the performance of deployed models

Preferred Qualifications

  • Experience in implementing projects involving end to end ML systems from development to deployment

  • Experience with relevant machine learning/deep learning frameworks such as Pytorch

  • Experience with querying and analyzing large scale data sets

  • Good understanding of optimization techniques and algorithm design

  • Experience with Modin/Vaex, Dask or PySpark, and Plotly

  • Proficient with relational and non-relational databases

  • Experience with GIT or other version control systems

  • Demonstrated experience in building analytical dashboards

  • Demonstrated experience in visually communicating insights

  • Excellent communication and teamwork skills

  • Experience working in a distributed team and communicating across geographic boundaries

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EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

If you would like more information about this role, please contact Qualcomm Careers (http://www.qualcomm.com/contact/corporate) .

EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

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