Our client is seeking a Data Scientist to usher in their own information revolution. They are specifically seeking an addition to the data and analytics team who is experienced in both the science and art of data. This 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 make important strategic and day-to-day decisions. This role will focus on innovation and building AI products that will drive efficiency and improve services to policyholders and injured workers. If you’d like to help shape the contours of what’s taking shape for this analytics and data group, as well as work at a flexible, mission-driven, community-oriented company, apply for this new machine learning engineer. We value diversity in the workplace and encourage women, minorities, and veterans to apply.
- 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 data 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.
- Master’s 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.