Data Science Intern at Johnson Johnson

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Description
At Johnson & Johnson, we use technology and the power of teamwork to discover new ways to prevent and overcome the world’s the most significant healthcare challenges. Our Corporate, Consumer Health, Medical Devices, and Pharmaceutical teams leverage data, real-world insights, and creative minds to make life-changing healthcare products and medicines. We're disrupting outdated healthcare ecosystems and infusing them with transformative ideas to help people thrive throughout every stage of their lives. With a reach of more than a billion people every day, there’s no limit to the impact you can make here. Are you ready to reimagine healthcare?
Here, your career breakthroughs will change the future of health, in all the best ways. And you’ll change, too. You’ll be inspired, and you’ll inspire people across the world to change how they care for themselves and those they love. Amplify your impact. Join us!
Qualifications
Johnson & Johnson is recruiting for a Data Science Intern at Digital & Data Science Group - JJSC located in listed locations or Remote.
Caring for the world, one person at a time has inspired and united the people of Johnson & Johnson for over 130 years. We adopt research and science -- bringing innovative ideas, products and services to advance the health and well-being of people.
The Machine Learning (ML) organization at J&J Supply Chain D&DS are hiring 4-6 student interns enrolled in advanced degrees in STEM areas. We are recruiting the interns for Summer 2023 or one school semester/quarter and expect the interns to conduct a research study for a given topic, explore data analysis followed innovative modeling and write a conference paper, white paper or blog post based on J&J publication policy.
The topics of projects are yet to define; however, the ML organization seek areas of interests based on the D&DS business scope, strategy, and current customer pipeline. The interns will be supervised and mentored by at least one Sr data scientist with relevant background.
We consider applicants with the following background as preferred candidates:
 Natural language processing (NLP), understanding (NLU), and generation (NLG) 
 Forecasting and Time-series analysis (preferably with supply chain experience) 
 Computer vision (CV) (preferably with defect detection or inspection projects experience) 
 Graph analysis, reinforcement learning (RL), classical ML, and Internet of Things (IoT) 
 Education: 
 Currently enrolled in degree program (MS or Ph.D.) in Electrical Engineering, Computer Science, Computer Engineering, Mathematics, or related field with specialization in ML, NLP, Deep Learning, Computer vision, data science or related fields. 
 Experience and Skills: 
 Strong understanding of programming languages such as Python and ML libraries and frameworks such as NumPy, SciPy, PyTorch and TensorFlow. 
 Practical ML experience 
 Familiarity working with cloud computing environment such as Azure, AWS, GCP, or Databricks 
 Preferred Qualifications 
 Research experience related to ML, deep learning (DL), NLP, CV and general DS 
 Published and/or presented papers at any recognized conferences or journals 
 GPA 3.7/4 or higher 
 PhD students in STEM 
At Johnson & Johnson, we’re on a mission to change the trajectory of health for humanity. That starts by creating the world’s healthiest workforce. Through cutting-edge programs and policies, we empower the physical, mental, emotional and financial health of our employees and the ones they love. As such, candidates offered employment must show proof of COVID-19 vaccination or secure an approved accommodation prior to the commencement of employment to support the well-being of our employees, their families and the communities in which we live and work.
Johnson & Johnson is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability.