Data Scientist
Company | Rocket Companies |
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Location | Detroit, MI, USA |
Salary | $Not Provided – $Not Provided |
Type | Full-Time |
Degrees | Master’s |
Experience Level | Mid Level |
Requirements
- 3 years of experience working with large data sets in one or more of the following environments – Hadoop, AWS, Azure or GCP
- 3 years of experience with statistical and data mining tools and methods
- 3 years of experience with supervised models (e.g., regression, neural networks) and unsupervised techniques (clustering, PCA, SVMs)
- 3 years of experience working with SQL
- 3 years of experience working in a UNIX environment
- 3 years of experience in at least one scripting language (e.g., BASH)
- 3 years of experience in Python and at least one strongly typed language (e.g., C++, Java, etc.)
- 3 years of experience with statistical packages
- 3 years of experience providing predictive and prescriptive analytics in a business setting
- Master’s degree in mathematics, statistics, computer science or a related field or equivalent experience
Responsibilities
- Design and implement metrics and testing methodologies to evaluate AI systems for responsible AI considerations
- Research and implement state-of-the-art techniques in responsible AI
- Perform disparate impact analysis on existing and new machine learning models
- Audit existing and new machine learning models for model performance, impact and reliability
- Develop tools for model developers to standardize model development lifecycle
- Write new functions or applications to conduct analyses
- Create and maintain documentation for model governance and regulatory compliance
- Collaborate with business stakeholders to translate governance requirements into technical specifications
- Contribute to the development of company-wide responsible AI guidelines and best practices
- Mentor team members on responsible AI practices and methodologies
- Apply sampling techniques to create representative datasets for model evaluation
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance
- Create graphs, charts or other visualizations to convey the results of data analysis
- Deliver oral or written presentations of the results of model evaluation and data analysis to stakeholders
- Communicate analyses, conclusions and solutions clearly to all audiences
- Develop and evangelize best practices for model development, evaluation and maintenance
- Drive the collection of new data and the refinement of existing data sources related to Responsible AI practices
- Mentor and train associate data scientists
Preferred Qualifications
- Experience with model explainability techniques
- Advanced understanding of data visualization libraries
- Advanced understanding of statistical methodologies for modeling and business analytics