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What kind of data are you working with?
Unstructured and structured data in the insurance and reinsurance industries.
What kinds of analytics are you using?
Predictive analytics such as optimization, Monte Carlo simulation and marginal pricing, using our proprietary high-performance computing architecture.
What are the problems your company is interested in solving?
Develop a generic analytical platform that can provide a high-performance framework in order to support a large variety of related, big-data analysis tasks having varying applications.
How did you get involved in your line of work?
Most of our team members have previous experience building real-time decision support systems at a highly quantitative reinsurance company.
What are you most proud of in your work?
Providing relevant client solutions that deliver high-resolution insights and are close to 100X times faster than other alternatives.
What are the biggest challenges in your line of analytics?
Lack of public information about framework approaches within our specific domain. So we have to experiment our way out by solving challenges.
What’s the best advice you can give someone interested in getting involved in a career in Big Data?
Get your hands dirty and do some data science. Start analyzing large data sets that are freely available on the net. Read up on what the top big data companies are doing. Take part in competitions at www.kaggle.com
What’s the best thing about doing Big Data in Nova Scotia that you want to share with the world?
Nova Scotia’s large population of highly educated individuals who possess specialized degrees is getting a further boost by Dalhousie University’s new Big Data Analytics Institute.
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