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R9605 Senior Data Scientist (Open)
Produces innovative solutions through the use of the most advanced data analytics from complex and high-dimensional datasets. Works with business partners to understand what the business needs and issues are to address. Applies advanced knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries to meet a variety of business challenges. Designs, develops, and evaluates predictive modeling frameworks, tools and advanced algorithms that lead to business solutions. Conducts the most complex and vital analytics work critical to the organization. Leads complex projects that yield actionable insights used by leadership to make strategic, data driven business decisions. Leads the communication of findings and recommendations to leadership and business partners. Leads implementation efforts. Mentors less experienced peers.
- Preferred: Master's Degree in Mathematics, Statistics, Physics, Computer Sciences or Engineering, or related field; PhD strongly preferred
Specialized Knowledge and Skills Requirements
- This position requires travel up to 10% of the time
Additional Job Information:
- Demonstrated experience providing customer-driven solutions, support or service
- Ability to work as part of a team and to communicate effectively.
- Mastery of a wide variety of programming languages and frameworks, demonstrating strong skills in the development, articulation and implementation of coding practices for the team.
- Demonstrated experience communicating complex findings in a clear and concise manor to senior management.
- Demonstrated experience developing and managing complex projects and effectively leading interdisciplinary teams to accomplish project goals.
- Demonstrated experience formulating, approaching, and solving complex analytical problems using a quantitative, scientific approach. Experience with a broad range of modeling techniques such as probabilistic graphical models, natural language processing, kernel methods, recommender systems, support vector machines, deep learning, media mix modeling, linear optimization, decision tree models, survival analysis, principal component analysis, and/or simulation modeling.
- Demonstrated experience working with large, complex datasets using big data technologies and script language.
- Extensive knowledge and understanding of managing data to scale using data summarization, query, and analysis software and tools.
We are looking for data science professionals who can help us transform the insurance industry. American Family’s Data Science and Analytics Lab uses advanced analytical techniques – machine learning, natural language processing, statistics, and geospatial analysis – with new sources of data to create the future of insurance. We are using data-driven insights to envision new products, services, and means of engaging customers, and to develop fundamentally new business models for insurance.
While we are part of a Fortune 500 company, we are more like a startup than a large corporate entity. Our small, agile team is a diverse mix of computer scientists, data engineers, developers, statisticians, and insurance domain experts. While we tackle a variety of insurance-related analytical questions, our focus is on creating a new future for insurance that incorporates the explosion of new data sources becoming available from mobile, social media, and IoT.
Depending on qualifications, candidates may be hired at a different level.
Offer to selected candidate will be made contingent on the results of applicable background checks.
Offer to selected candidate is contingent on signing a non-disclosure agreement for proprietary information, trade secrets, and inventions.
Relocation assistance is available.
- Creates innovative vision and strategy, along with business application and modeling framework for new datasets, and leads the discovery of insights and relationships from large/complex datasets through investigative research using advanced mathematical and/or statistical techniques.
- Explores data using a variety of advanced statistical techniques to proactively identify relationships, create insights and answer business questions or guide future model development.
- Build the hypothesis, identify research data attributes and determine best approach to address business issues.
- Combines business acumen with mathematical capabilities to build complex predictive models to support business partner objectives and business needs.
- Builds complex programs for running statistical tests on data and for understanding correlation of various attribute.
- Incorporates findings and provides industry and competitor insights as part of model development and enhancement
- Interacts with leadership to assist in the development of strategic direction for the business or business partners.
- Researches and maintains awareness of industry best practices and business strategies.
- Proactively brings in new and innovative ideas and approaches to develop business solutions.
- Monitors industry and competitor trends to determine potential impact to predictive models.
- Incorporates findings and provides industry and competitor insights as part of model development and enhancement.
- Identifies, leverages and develops expertise in emerging technologies, open source tools, and harnesses new techniques.
- Networks with and contributes thought leadership to the broader external analytics community. Builds awareness of leading techniques, tools, and data resources.
- Leads complex research or analytics projects related to large, complex business initiatives. Applies expert knowledge of emerging trends and industry practices.
- Functions in a collaborative and consultancy role. Routinely leads discussions with senior management.
- Interacts and leads discussions with company senior leadership to inform on industry trends and emerging research topics. Serves as internal expert for new areas of analytics exploration.
- Leads the development of new analytical and data science capabilities.
- Mentors less experienced data science professionals.
- Serves as internal thought leader, and provides knowledge transfer and training on new modeling tools and methodologies to less experienced staff.
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