Job Description
Verisk’s Data Science Excellence Program (DSEP) is a 3-year rotational program designed to develop the next generation of data scientists and data engineers. The program consists of two 18-month rotations within Verisk’s various analytics teams as a full-time Verisk employee. As a DSEP Data Scientist, you’ll receive hands-on analytics experience doing everything from data wrangling, querying, modeling, visualizing, and productizing as you work in the insurance business area. 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 that can be put into production. As a member of a project team, you will be exposed to some of the data challenges faced at Verisk’s operations potentially including large-scale data analysis, real-time data analysis, and anomaly detection. Data sets of interest include insurance policy and claims data, imagery and documents.
Responsibilities
- Manipulate, analyze, visualize, and model data of varying volume and velocity with some guidance
- Work with cross-functional peers and management to see a project through to deployment
- Communication of complex quantitative analysis in a clear, precise, and actionable manner
- Demonstrate a passion for empirical research and resourcefulness for problem-solving with data
- Continue learning new technologies, business skills, and domain knowledge to ensure a successful career
- Participate and help organize various innovative events such as hackathons and other competitions
Qualifications
- Currently starting the penultimate year of a Bachelor's or Master's degree in a technical field of study (e.g., statistics, business analytics, econometrics), with an expected graduation date in summer 2026
- Strong programming capability in a common language such as Python and its’ associated ecosystem of open-source libraries
- Proficient in SQL. Understanding of NoSQL query languages a plus
- Basic understanding of software development practices such as versioning, testing and continuous deployments
- Understanding of one or more machine learning or statistical concepts
- Supervised, unsupervised, semi-supervised learning scenarios
- Optimisation 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
Experience in one or more of the following:
- Real-world use cases that solved a problem by applying machine learning and statistical modeling on structured and/or unstructured data
- Computer vision working with images, videos, or point clouds
- Natural language processing working with short or long-form text
- Large scale mathematical programming and/or optimization problems
- Other deep learning applications and architectural designs such as graphs or multimodal problems
