SAIF Corporation
Data Scientist
SAIF Corporation, Salem, Oregon, United States,
Working with data is most certainly a science. It takes a scientist to analyze, evaluate, and maintain data so that it can be used to build, validate, and deploy machine learning (ML) models that help SAIF make strong business decisions.But at SAIF, working with data is also an art. To collaborate with partners from across the organization, to interpret data in a way that makes it understandable and accessible to everyone, and to imagine the many ways that it can make people’s lives better – that is art.SAIF is seeking an addition to our data and analytics team who is experienced in both the science and art of data. Our new data scientist will work with the business units to understand key business challenges and design artificial intelligence (AI) solutions. You’ll help create machine learning models to help SAIF make important strategic and day-to-day decisions.Your role will focus on innovation and building AI products that will drive efficiency and improve services to policyholders and injured workers in Oregon. Apply today.RESPONSIBILITIES:
Analyze business problems and prep data for use in AI models.Evaluate Machine Learning (ML) models and decide appropriate use of models or combination of models to provide the most effective and efficient solution for the business.Data preparation, feature engineering, development, deployment, maintenance, and tuning of Machine Learning (ML) models.Estimate the potential impact/value of different models and the feasibility of integrating them into the current environment.Interpret problems and provide solutions using data analysis, optimization, appropriate testing techniques, and advanced analytics (including machine learning).Retrieve, prepare, and process a rich variety of data sources such as operational, financial, internal/external documents, news, and social media.Perform Statistical Natural Language Processing to mine unstructured data, including using methods such as document clustering, topic analysis, named entity recognition, document classification, and sentiment analysis.Provide demonstrable evidence of model accuracy and output validation, including supporting documentation of the underlying analysis.Explain findings, formulate conclusions, and deliver recommendations for next steps based on model results. Identify and investigate unreasonable results and provide possible solution alternatives.Explore diverse perspectives and consistently behave sensitively toward differences in cultural norms, expectations, and ways of communicating. Work effectively with others who have different perspectives, backgrounds, and/or work styles.Continually sustain the Inclusive Leadership Certification (ILC) through the Explorer level on an annual basis.REQUIRED QUALIFICATIONS:
Experience/Education: Masters degree in Computer Science, Mathematics, Economics, Statistics, or other quantitative field plus 3 years of applied business experience required; or PhD plus 2 years of applied business/non-academic experience preferred.Experience with very large analysis datasets and enterprise-scale database systems.Experience with machine learning models, Natural Language Processing (NLP) models.Proficient with languages like R, Python and familiarity with libraries NumPy, PyTorch, TensorFlow.Other combinations of skills and experience may be considered.Next step:
To receive consideration, please submit your resume with a cover letter by the close of this recruitment. We want your submission to count, so be sure it’s complete.This recruitment will close on Thursday, September 17, 2024.If a sufficient number of qualified applications are received, this recruitment may close early.
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Analyze business problems and prep data for use in AI models.Evaluate Machine Learning (ML) models and decide appropriate use of models or combination of models to provide the most effective and efficient solution for the business.Data preparation, feature engineering, development, deployment, maintenance, and tuning of Machine Learning (ML) models.Estimate the potential impact/value of different models and the feasibility of integrating them into the current environment.Interpret problems and provide solutions using data analysis, optimization, appropriate testing techniques, and advanced analytics (including machine learning).Retrieve, prepare, and process a rich variety of data sources such as operational, financial, internal/external documents, news, and social media.Perform Statistical Natural Language Processing to mine unstructured data, including using methods such as document clustering, topic analysis, named entity recognition, document classification, and sentiment analysis.Provide demonstrable evidence of model accuracy and output validation, including supporting documentation of the underlying analysis.Explain findings, formulate conclusions, and deliver recommendations for next steps based on model results. Identify and investigate unreasonable results and provide possible solution alternatives.Explore diverse perspectives and consistently behave sensitively toward differences in cultural norms, expectations, and ways of communicating. Work effectively with others who have different perspectives, backgrounds, and/or work styles.Continually sustain the Inclusive Leadership Certification (ILC) through the Explorer level on an annual basis.REQUIRED QUALIFICATIONS:
Experience/Education: Masters degree in Computer Science, Mathematics, Economics, Statistics, or other quantitative field plus 3 years of applied business experience required; or PhD plus 2 years of applied business/non-academic experience preferred.Experience with very large analysis datasets and enterprise-scale database systems.Experience with machine learning models, Natural Language Processing (NLP) models.Proficient with languages like R, Python and familiarity with libraries NumPy, PyTorch, TensorFlow.Other combinations of skills and experience may be considered.Next step:
To receive consideration, please submit your resume with a cover letter by the close of this recruitment. We want your submission to count, so be sure it’s complete.This recruitment will close on Thursday, September 17, 2024.If a sufficient number of qualified applications are received, this recruitment may close early.
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