Data Science Internship - Cork, 2024

Key Skills

Algorithms, Dask - Python library, Data science techniques, Deep Learning, Design, Effective communication skills, Git, Large data sets, Machine learning techniques, PySpark, Python Programming, PyTorch, SQL, Teamwork

Job Description

Qualcomm is a company of inventors that unlocked 5G ushering in an age of rapid acceleration in connectivity and new possibilities that will transform industries, create jobs, and enrich lives. But this is just the beginning. It takes inventive minds with diverse skills, backgrounds, and cultures to transform 5Gs potential into world-changing technologies and products.

We are looking for a Data Science intern who can perform predictive analytics, develop, and productionize machine learning models, large scale data analysis and data visualizations. Candidate will be part of a global cross-functional team that’s responsible for the development of machine learning applications using state-of-the-art algorithms for Qualcomm engineering teams. As part of this team, you will have opportunity to explore and work towards applied machine learning.

As an intern, you should be eager to learn and explore large-scale data sets, deriving insights using statistical analysis, probabilistic estimation techniques and building machine learning systems. Proficiency in python, machine learning and deep learning frameworks, querying/transforming large datasets data and visualizing datasets to present the story from data is required.

Minimum Qualifications

• Bachelor’s degree in computer science, Engineering, Statistics, or Operations research with relevant experience in applied machine learning
• Strong knowledge of SQL, Python, Machine learning and Deep learning frameworks
• Working knowledge of experiment design and hypothesis testing

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

• Master’s degree in computer science, Engineering, Statistics, or Operations research with relevant experience in applied machine learning
• Experience in implementing 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 visually communicating insights
• Excellent communication and teamwork skills
• Experience working in a distributed team and communicating across geographic boundaries

*References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.

Applicants: If you are an individual with a disability and need an accommodation during the application/hiring process, please call Qualcomm’s toll-free number found here for assistance. Qualcomm will provide reasonable accommodations, upon request, to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. Qualcomm is an equal opportunity employer and supports workforce diversity.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.