Data Scientist

Job Overview
We are looking for a Data Scientist who will support our actuarial department with insights gained from analyzing company data. The candidate must be proficient in using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. Must have experience using a variety of data mining or data analysis methods, with the use of different variety of data tools, building and implementing models, using or creating algorithms and creating simulations. Must be willing to work with a wide range of stakeholders. And the candidate who has passion for discovering solutions hidden in the large data sets and willing to work with stakeholders to improve business outcomes will be the best fit for the role.

Responsibilities:
• Work with stakeholders throughout the department to identify opportunities for leveraging company data to drive business solutions.
• Mine and analyze data from company databases to drive optimization and improvement of product development, processes and business strategies.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling
• Develop testing framework and test model quality.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Develop processes and tools to monitor and analyze model performance and data accuracy.

Qualifications:
• At least 2-10 years of relevant working experience in insurance industry, preferably general insurance
• Strong problem solving skills with an emphasis on product development.
• Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
• Experience working with and creating data architectures.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.
• With experience in manipulating data sets and building statistical models
• Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools is an advantage:
• Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
• Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.
• Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
• Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
• Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.