Data Scientist Intern - San Jose (STEM Ideas Program)
We are not able to support international students who require sponsorship after graduation
Wonder what’s within the Life Sciences Platform ?
Danaher`s Life Sciences Platform is a global leader uniquely positioned to industrialize biology reducing time and cost to market of biologics and improving access to new life saving therapeutics. Our Life Sciences business provides products under a variety of brands, including Beckman Coulter Life Sciences, Cytiva, Pall, and Integrated DNA Technologies. Learn more at: https://jobs.danaher.com/global/en/within-life-sciences
Job Description
You will be a part of the Life Sciences Digital Data Science Leadership Team and report to the leader of that organization. You will work on innovative design and development projects of scalable Machine Learning (ML) solutions that help our customers decrease the time it takes to bring new, lifesaving therapies to market. If you thrive in a fast paced, multi-functional role and want to work to build skills in both data science and life sciences —read on.
Responsibilities
- Help acquire, clean and structure data from multiple data sources and maintain databases/data systems.
- Identify, analyze, and interpret trends or patterns in complex data sets
- Create prototypes using the latest in AI/ML techniques and test predictive algorithms.
- Interpret data, apply statistical analysis and modeling techniques and provide ongoing reports
- Be a good teammate by working collaboratively with cross functional teams including Data Engineers, Product Managers and/or customers.
- Above all, have a curious mind and be a fast learner
Requirements
- Currently enrolled in a Masters’ program in Computer Science, Mathematics, Statistics or a related field.
- Experience in Python, SQL
- Knowledge of probability, statistics and machine learning theory including: Clustering, Decision Trees, Logistic Regression, Dimensionality Reduction, Random Forests, and Deep Learning Networks.
- Readiness to work with engineering teams to develop AI Models leveraging exploratory data analysis