Analytic Scientist
Do you have the desire to play a critical role in driving data-based business outcomes? At Nationwide, our Analytic Scientists are responsible for modeling complex problems, discovering insights and identifying business opportunities using scientific research methods, statistics, machine learning and data visualization techniques. They participate in all phases of the analytic lifecycle, from research design, data collection and data processing to model building, deployment and presentation of results. We value a commitment to lifelong learning and strong quantitative judgment. If you are a methodological generalist who is adept at applying your technical skill set to a wide range of business applications, we want to know more about you! As a Specialist, you'll often work independently and seek guidance and support from their manager as needed. You'll participate in all phases of the analytic lifecycle, from research design, data collection and data processing to model building, deployment and presentation of results. We'll count on you to be fully proficient with common statistical and machine learning techniques and exhibit some knowledge of advanced modeling techniques and their application. Job Description Key Responsibilities:
- Completes well-defined objectives associated with the design, development, implementation, and monitoring of statistical and machine learning models independently.
- Works with business partners to craft an analytic strategy that meets their needs and delivers timely results.
- Integrates relevant internal and external research findings to generate hypotheses and help business partners make informed decisions.
- Applies advanced quantitative techniques to analyze any given data structure.
- Builds predictive and explanatory models to generate actionable insights and practical solutions to business problems.
- Crafts deliverables that provide clear and concise summaries of findings and recommendations using impactful storylines and data visualization geared to both technical and non-technical audiences.
- Upholds a high standard for methodological rigor, sound statistical inference, and robust model validation.
- Quantitative judgment: Experience building and deploying machine learning and/or statistical models.
- Research methods: Knowledge of multiple quantitative research and analysis approaches and their tradeoffs.
- Programming ability: Python, R, SQL, or any other transferrable language (MATLAB, Java, etc.).
- Communication skills: Reading/writing/speaking about predictive modeling to stakeholders ranging from business partners to modeling experts. Capable of developing compelling stories and distinctive data visualizations.
- Passion, inquisitiveness, creativity, self-starters and team builders.
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