*Telecommuting role to be performed anywhere in the U.S.
Build data science solutions for business challenges including customer propensity, product forecasting, and recommender systems. Use machine learning, data mining, and statistical methods to distill meaningful insights from large, complex dataset.
What You Will Do:
- Participate in end-to-end development, from requirements gathering to validation and implementation.
- Work closely with data engineering and ML Ops functional roles to operationalize data science solutions through automation and continuous delivery.
- Implement monitoring for data science solutions to identify model degradation, data drift, and concept drift, and ensuring that the model is maintaining an acceptable level of performance.
- Directly engage with key decision makers across the business to iterate, test, and deliver solutions that improve the way we operate.
What You Will Bring:
- Bachelor's degree (U.S. or foreign equivalent) in Computer Science, Analytics, or related field and three (3) years of experience in the job offered or related role.
- Must have three (3) years of experience with: developing production-grade data science models; statistics and machine learning models and algorithms; producing well-documented, well-formatted code using object-oriented design principles, including Python; feature engineering using statistical techniques; data querying and transformation, including SQL; and working with engineering and ML Ops team members to develop and operationalize data science solutions, including migrating prototypes into production environments.
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The salary range for this position is $147,470 - $243,350/year. Actual offer will be based on your qualifications.
Pay Transparency
Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat’s compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience.
