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Your future begins now. Verisk‘s Summer Internship Program is designed to provide you with real work experience, professional development, and networking opportunities.
We are hiring in several locations across the US for this internship. Should you perform well in the internship, you may receive an offer to join our full-time Data Science Excellence Program (DSEP) following graduation. As DSEP is a rotational program, we highly suggest that you apply to this internship if you are open to future relocation.
What you could learn:
As a Data Science Intern, you’ll receive hands-on analytics experience doing everything from data wrangling, querying, modeling, visualizing, and productizing as you work in business areas including insurance, finance, energy, and climate. You will help our clients in decision analytics, forecasting, and risk management.
The work includes the creation of both proof-of-concept demonstrations to illustrate specific technologies and algorithms as well as robust operational systems than can be put into production. As an active member of project teams, you will be exposed to some of the data challenges faced at Verisk’s operations including large-scale data analysis (petabytes), real-time data analysis, and anomaly detection. Data sets of interest include large imagery and physical science data, payments industry data, and insurance data.
Verisk provides our interns with mentorship, training, engaging program events, and valuable exposure to the senior analytics and business leaders guiding our company. If you have a strong technical background, enjoy ongoing learning and innovative thinking, and strive to actively participate in knowledge-sharing and open collaboration, we hope you will consider joining us.
What we’re looking for:
Work availability requirements:
- December 2022/ May 2023 graduate pursuing an MS degree in Data Science/Analytics, or an undergraduate degree in similar concentration
- Must be able to commence working without restrictions in June 2022 for a summer internship.
- Strong programming capability in a common language such as python or R and their associated ecosystem of open source libraries
- Must be proficient in SQL, understanding of NoSQL query languages a plus
- Interest in learning/ using machine learning and statistical concepts (Supervised, unsupervised, semi-supervised learning scenarios; Optimization and loss functions; Evaluation of classification, regression, and other model results; Probability distributions and unbalanced samples; Dimensionality problems, sampling, and Bayesian methods; Missing values and imputation)