Data Science - R&D Internship - Summer 2017
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The Data Science Research and Development team is responsible for developing the fundamental data science methods, techniques, and best practices that power the mission of our company. Our diverse work includes predictive analytics, algorithm development, experimental design, natural language processing, visualization, and survey research. As an intern on our Chicago-based Research and Development team, you will learn modeling strategy, research design, and software engineering from data scientists on the cutting edge of the field. You will work on collaborative projects through which you will make real contributions to the best practices that back our products and our consulting. To help you learn and succeed, you will be paired with a data scientist mentor from our team — we strive to grow the skills of our interns.
Past interns have worked on a variety of projects including:
- Applications of neural network autoencoders on large, sparse datasets from social media, television viewership, and medical diagnostics
- MCMC code development and Bayesian statistical modeling of time series data from surveys
- Development of production code for resource optimization
We are looking for individuals from a diversity of backgrounds with demonstrated quantitative and problem-solving skills. We value creativity, hard work, and on-the-job-excellence and offer competitive compensation. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States.
Juniors, seniors and graduate students only. Our paid summer internships are a full-time, 10-12 week commitment.
MINIMUM QUALIFICATIONS- Junior standing in undergraduate degree program in statistics, computer science, economics, physics or other quantitative field
- Experience using applied statistics or machine learning
- Proficiency with Python or R
- Experience working with imperfect data
- Passion and eagerness to constantly learn and teach others
- Masters or PhD student in statistics, computer science, economics, physics or other quantitative field
- Specialization in a particular area of statistics or machine learning, e.g. neural networks, Markov Chain Monte Carlo, network analysis, data engineering, natural language processing, optimization, etc.
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