Remote Intern

About the Program 

Our internships center around hands-on mentorship, capstone project, interactive sessions, and small group discussions. As a data science intern for one of our three Data Science departments (Health, Life Sciences and Research) your activities will span one or more of the following: researching state-of-the-art methods, designing, writing code and running experiments to test hypotheses, perform validation of the system, developing demo applications. You will work closely with the diverse team of data scientists and domain experts. During this internship, you’ll be paired with a core expert group who will mentor you as you tackle real-world projects in respective domains. You’ll also be able to access our physical and virtual educational resources, attend guest speakers and social events, and get a sense of what it would be like to work here full time. 

If you’re thinking about a career in data science, technology, clinical analytics, life sciences, or research, look no more. If you have a curious mind, a collaborative nature, and a passion for solving interesting problems, we have a feeling you’ll fit right in. 

About the Position 

As a Data Science intern, you’ll work side by side with full time employees to learn how we identify market signals, analyze large datasets, build and test models, create new strategies, demonstrate technology proof-of-concepts and write code to implement them.  

The problems we work on rarely have clean, definitive answers, hence providing an opportunity to cross-collaborate. Through your experience we hope that you will better understand the diverse array of research challenges considered every day, from reasoning about how best to analyze very noisy datasets to building practical models using various state of the art technologies.  

Education and other qualifications 

• Master or PhD in computer science, data science is required.  

Skills 

• Strong understanding of ML/NLP pipelines, proficiency in Python. Hands-on project development experience with supervised and unsupervised learning; model building, validation, and testing using state of art ML algorithms such as random forest, SVM, Logistic Regression, Bayesian modeling would be a plus.  

• Good to have experience or knowledge of building, fine-tuning and deploying deep learning models, neural networks, state-of-the-art transformer language models, GenAI. 

• Experience or interest in working with “big data” and applying advanced algorithms in Healthcare, Life Sciences or any Research domains. 

• Experience using *nix systems, open-source software, libraries and jupyter notebook hubs is required. 

Behaviors 

• Ability to drive new developments and implement process changes and disruptive technologies in the organization.  

• Self-motivated and a team player. 

• Enjoys being part of an agile, global team with members in India, Europe and the US. Great collaborator. 

• Good communication and documentation skills  

• Adopts pragmatic approach when choosing and implementing the right technologies to solve a problem and develops success metrics. 

• Thirsty for knowledge and keen to share learnings with the team. 

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Elsevier is an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form: https://forms.office.com/r/eVgFxjLmAK , or please contact 1-855-833-5120.

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