Senior Data Scientist

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Assurant

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specialty insurance • extended service products and related services • renters insurance • lender-placed homeowners insurance • flood insurance

10,000+

💰 Post-IPO Debt on 2023-02

Description

Creating Value Through Data (15%) • Produce clear, insightful, understandable work products (visualizations, reports, presentations, etc.) to outline business opportunities and actionable recommendations. • Transform data into insights through leveraging internal and external tools (e.g., Python, GitHub, IDE, Spark, R, SQL, Excel, Power BI, etc.) to identify and quantify opportunities. • Build studies that add substantial value to the decision-making process through proactive data analysis, reporting, and research. Model Development (40%) • Develops machine learning solutions for complex business problems; examine data and develop use cases to identify artificial intelligence/machine learning solutions. • Provides feedback to product and engineering teams on machine learning solution design and development and communicate the approach and implementation of the machine learning solution. • Works independently with mentorship from senior team members and/or leadership of the Data Science team on leveraging existing frameworks and models for known use cases around machine learning. • Devises new algorithmic approaches to solving difficult quantitative problems using large scale enterprise data sources. Communicating Insights (10%) • Presents analysis and resulting recommendations to senior management. • Leverages data to present compelling business cases to optimize investments and operations. • Communicates and educates both technical and non-technical employees on analytics and data-driven decision making. Project Management (15%) • Leads projects and assists in development of project plans, conducting analysis/modeling, hypothesis testing, presenting complex information for various audiences in simplified terms, and identifying next steps and future opportunity. • Mentors team members in technical proficiency, code reviews, and business acumen. • Collaborates with team members to prioritize requests requiring multiple resources for thorough project completion within stated timelines. Support Data Strategies (10%) • Remains abreast of developments in the field(s) of insurance, management, and data sciences by attending self-development programs, interacting with peers, and reviewing pertinent literature. • Incorporates advancements when practicable and cost effective. • Participate and drive data modeling and governance best practices. • Proactively engages internal and external teams to discover areas of analytical needs. • Advances company-wide understanding and implementation of AI and machine learning as well as matures the team’s practices and procedures, leveraging learnings from existing implementations. • Participates in the talent acquisition process by screening and interviewing candidates at all levels. Product Leadership (10%) • Work cross-functionally with business owners to develop innovative advanced analytics products that will increase customer experience, capitalize growth opportunities, deliver competitive advantage and improve decision making. • Analyze effectiveness of analytical products and services to constantly improve tools, procedures, and workflows that minimize risk and enhance customer experience. • Ensures data and model governance is established to comply with internal audit requirements and ensures compliance with data governance and data privacy policies. • Drive Analytics as a Product (AaaP) and provide thought leadership to Assurant’s Data Analytics COE, questioning traditional wisdom, current standard practices, and capabilities.

Requirements

Overall Work Experience: 8+ Years • Min 6+ years - Experience in data science, statistics, applied mathematics, data management, business intelligence, or related fields. • Min 6+ years - Experience with data science tools (e.g., Python, GitHub, IDE, Spark, R, SQL, Excel, Power BI, etc.) and relational database software. • Min 5+ years - Experience in data analysis that includes translating insights into recommendations. • Min 3+ years - Experience in an analytical role involving data extraction, analysis, statistical or machine learning modeling and communication. • Master’s Degree in Statistics, Economics, Applied Mathematics, Computer Science, or Information Management; or equivalent is required.