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The Global Risk Solutions’ Advanced Analytics Hub is seeking an experienced data science leader to develop and deploy innovative and cutting-edge models to solve business problems in new subject areas. In this role, you will have an opportunity to build a new team responsible for expanding the AA Hub’s capabilities and reach in new areas like Distribution and Portfolio Management. You will manage data science engagements from beginning to end - ideation with business partners to final system implementation. Projects will vary in nature, complexity, location, and duration creating a dynamic environment with ample opportunities to learn and solve complex business challenges. You will also be expected to contribute to the advancement of modeling techniques and toolsets for improving modeling productivity and model deployment. Knowledge of insurance and Actuarial principles is a plus.
- Manage 5-6 data scientists and analysts, as well as help manage aligned tech resources
- Engage with business partners to understand problems/aspirations and develop data science solutions that address business needs.
- Guide analysts in preparation of modeling and other analysis. Seek out reference materials and experts to help interpret insurance data.
- Provide technical expertise to set project direction, resolve issues encountered in modeling projects, and develop jr staff. Perform complex modeling.
- Present findings and make actionable business recommendations that influence decisions and/or customer satisfaction.
- Effectively communicate results in written, oral and presentation formats. Build effective relationships with business partners.
- Regularly engage with the data science community and participate in cross-functional working groups. Actively participate in peer review and quality check processes.
- Research and deploy Machine Learning (ML) techniques. Participate in the broader ML community to stay current with the latest techniques. Engage with staff within and beyond the predicative analytics team, training and advocating for the use of ML techniques in other business areas.
- Attract and develop top talent. Create an inclusive, engaging team environment.
- Competencies typically acquired through a Ph.D. or Master’s degree (in Applied Mathematics, Computer Science, Statistics, or other quantitative field of study) and 1 or more years of insurance industry experience.
- Prior managerial experience in data science or advanced analytics is desired
- Broad understanding of core statistical and ML techniques with experience analyzing data and building models in a statistical programming language (e.g., SAS, R, Python, etc.).
- Advanced proficiency in Python, Java, C/C++, or similar language, along with standard ML libraries and experience in working in cloud-based environments (e.g., Azure, AWS, etc.), is another plus.
- Hands on experience with ETL tools, Hadoop, Spark, Hive/Pig, and HBase, is also a plus.
- Ability to quickly grasp new concepts and technologies and adapt to changes and demands in fast-paced, dynamic environment, including drawing conclusions and making decision from imperfect and disparate datasets.
- Excellent analytical, strategic, project management, decision-making and problem-solving skills.
- Strong written and verbal communication skills, as well as proven ability to effectively present technical concepts to non-technical individuals within and outside the organization.
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