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- Develop and validate advanced analytic models
- Build datasets to support model development
- Collaborate with other team members on scoping solutions and project decision points
- Compile data exhibits to support models
- Present on technical topics to peers, leadership, and other stakeholders
- Communicate with business partners that require articulation of the work in non-technical terms
- Lead/mentor other Data Scientists and other technical work teams
- Make strategic recommendations on data collection, integration and retention requirements, incorporating business requirements and knowledge of best practices
- Perform advisory/consulting work for the organization, including specialized or innovative areas
- Serve as a peer reviewer to other model development teams
- Work on complex problems of diverse scope where analysis of situations or data requires evaluation of intangible variance factors
- Establish and leverage a network of associates with business domain and data expertise by navigating the organization effectively
- Instill a business-oriented mindset that drives the science and research agenda
- Develop and initiate technical standards through interactions with professional societies
- Be recognized by others as an authority/professional resource in his/her area of expertise
- Build and maintain a relationship with the open source community by creating and contributing to open source data science software initiatives
- Must have a Master's Degree in Statistics, Data Science or similar field
- Programing background in SAS, R and/or Python with emphasis on techniques relevant to predictive modeling such as; data set development, cleaning, EDA, and utilizing modeling procedures.
- Experience with model feature creation, selection and value imputation.
- Broad experience building different types of advanced analytic solutions, including some of the following: time series analysis, cluster analysis, tree based algorithms, generalized linear models, and neural networks.