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Location: 4900 Tiedeman Road - Brooklyn, Ohio 44144-2302 ABOUT THE JOB (JOB BRIEF) The Data Science Senior Manager is primarily responsible for leading a quantitative analytics team in support of quantitative analysis including model development, validation, and maintenance. This role must establish priorities for the team, assign and define the work to the right resources, and understand the strengths and opportunities of the team to ensure the group meets and exceeds expectations. This role is responsible for owning modeling practices, methods, and techniques as well as for influencing data strategy with a focus on leveraging both current and emerging technologies and applications. The Data Science Senior Manager acts as a leader, strategic advisor and credible thought partner to senior / executive level business partners. This position is also responsible for managing the integration of activities within and across teams as well as effectively manage, coach, develop, and guide a team of professionals to anticipate business needs, recommend solutions that are both effective and efficient, and communicate the right message. ESSENTIAL JOB FUNCTIONS Provide strategic consultation and thought leadership to senior / executive level business partners Anticipate business partner needs Drive the output of the team - ensure "executive ready" work product in alignment with business priorities Influence / impact strategy for data sourcing Anticipate emerging needs; identify industry data trends and technologies Proactively coach and develop others on building technical skills Promote the group and their capabilities to stakeholders Effectively collaborate and partner at all levels of the organization; guides, advises, challenges, and influences to drive organizational impact Provide solutions based on "connecting the dots"; leverage business insights to align, develop, and build holistic strategies and solutions that align with LOB priorities and consider knowledge of cross-LOB interdependencies REQUIRED QUALIFICATIONS Master's degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 6 years minimum of relevant experience; or Bachelor's degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 7 years of relevant experience DATA LITERACY Ability to: Influence / impact strategy for data sourcing; can anticipate emerging needs to be incorporated into strategy Lead discussions about pros/cons of applications with senior leadership Monitor industry trends and direction of data analysis technologies TECHNOLOGY & TECHNIQUES Advanced Microsoft Office Suite SQL/NoSQL Relationship data structure Selecting and retrieving data including unstructured data retrieval, archival, and ETL Databases Advanced Python/R/SAS: Databases Efficient coding Can build strong code controls and translate code into high-level commentary Understanding of and ability to leverage: Cloud-based computing Distributed computing MODEL BUILDING & MAINTENANCE Ability to: Establish standards and best practices; forecast future modeling tools / techniques Identify, employ, and evangelize emerging techniques from industry / research Coach others on data modeling methods / techniques Facilitate sessions for complex data models Assess and understand risks; contingency plans Communicate observations to senior executives Translate technical observations to a non-technical audience EXPECTED COMPETENCIES Leadership: Typically manages team of professionals; Resources and role model for broad team, beyond direct reports; Manages integration of activities within