** Please NO Corp to Corp
We are committed to providing valued-added services to customers and improving efficiency through enhanced capabilities in data and advanced analytics. This hands-on technical role is critical to improving operations, expanding product offers, and servicing the life insurance industry. It also has management responsibilities.
MINIMUM QUALIFICATIONS AND REQUIREMENTS
GENERAL DUTIES AND RESPONSIBILITIES
- Education: A master’s degree in a quantitative field such as statistics, mathematics, computer science, engineering, and physics. Ph.D is plus.
- Experience: 6 years of relevant experience in insurance, banking or other financial industries for a master degree holder, or 4 years for a Ph.D. holder.
- Must be proficient in SQL
- Must be expert in at least one of the following - R, Python, SAS
- In-depth knowledge of statistical techniques including:
- GLM (multiple regression, logistic regression, log-linear regression, and variable selection)
- Multivariate analysis - Clustering, factor, principal component
- Time series forecasting
- Survival analysis, and so on.
- Understanding of Machine learning (e.g. random forests, support vector machines, gradient boosting, etc.), Natural Language Processing and Deep Learning (e.g. CNN) techniques
- Experience in building predictive models using large datasets
- Experience with data ETL, overcoming challenges in a fragmented data environment and ensuring data quality
- Experience applying advanced analytics to solve business problems and drive business results
- Rich knowledge of the business of life, health, or property/casualty insurance industry.
- Proven project management skills; proven ability to plan, execute and control a project, establishing realistic estimates and reporting metrics, effectively allocate limited resources, and track record in meeting deadlines
- Excellent verbal and written communication skills; strong ability to explain technical results to technical and non-technical audiences
- Strong communicator who can deal effectively across all departments at all levels
- Strong negotiation, conflict resolution, and influencing skills
- Ability to coach, direct and develop individuals to achieve individual, departmental and company goals
- Collaborate with business partners and customers to understand business needs, assess opportunities and assist in new product development
- Apply advanced analytics skills and business knowledge to design and develop analytic solutions for internal and external customers
- Perform data ETL, query, merge, sampling, and quality checks on large datasets from diverse sources
- Perform variable reduction, selection, clustering, imputation, grouping, and customization
- Select analytic technique(s) most appropriate for the problem (e.g GLM, survival analysis, time series, multivariate analysis, ML, NLP, and DL etc.) and develop candidate models
- Perform model validation to compare lift, accuracy, reliability and stability of models, and select the final solution
- Work with deployment team to implement final models in production
- Develop performance metrics, automate monitoring procedures, and update models as needed
- Develop visualization and present analytic results to business partners, senior management and customers
- Stay current with the latest analytical skills, technological innovations and insurance developments; serve as a mentor to other teammates