Within GRM US Insights and Solutions, the Advanced Analytics & Modeling (AA&M) group leads the development and delivery of predictive analytics tools and insights to enable data-driven strategic decision-making. This includes the application of AI and machine learning (ML) techniques to achieve business plans. Team TIGER is one AA&M team supporting GRM US Claims. TIGER is looking for an Analyst I or Data Scientist, who will help build cutting-edge predictive modeling capabilities (such as computer visioning, NLP, deep-learning, etc.), as well as manage and enhance existing predictive models and pilots.
Responsibilities will include:
- Apply data science techniques
- Gain confidence in skill application using analytics and data science techniques to manipulate large structured and unstructured data sets in order to generate insights to inform business decisions
- Identify and test hypotheses, ensuring statistical significance, as part of building predictive models for business application
- Translate quantitative analyses and findings into accessible visuals for non-technical audiences, and provide a clear view into data interpretion
- Gain experience in enabling the business to make clear trade offs between and among choices, with a reasonable view into likely outcomes
- Assist in customizing analytic solutions to specific client needs
- Be responsible for smaller components (low to moderate complexity) of complex projects
- Engage with the Data Science community
- Participate in cross functional working groups
Please note this posting is open to mulitple locations or remote. Compensation will vary based on experience, education and location.
- Strong predicitive modeling experience required
- Advanced skills in predictive analytics tools, SAS, SQL, Python or R required
- Data extraction and manipulation skills, EDA, transformations, and general linear models (GLM)
- ML, deep learning, NLP modeling
- Demonstrated ability to exchange ideas and convey complex information clearly and concisely
- Has a value driven perspective with regard to understanding of work context and impact
- Competencies typically acquired through a Master`s degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) if no professional experience; or a Bachelor`s degree and 3+ years of relevant work experience
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