redhorsecorp - Redhorse Corporation - Senior Data Scientist
Requirements
• US citizen with a Secret US government clearance. Applicants who are not US Citizens and who do not have a current active Secret security clearance will not be considered for this role. • Bachelor’s degree in a STEM field or proven equivalent professional experience. • 4 years of experience including applied NLP, data labeling, entity or keyword extraction, and related topics • Understanding and use of various statistical distributions and use for data modeling • Ability to foster positive business relationships • Strong communication skills capable of presenting technical findings to diverse audiences. • Must be a motivated self-starter who can take direction and execute without constant monitoring. • Experience with Databricks, PySpark, SQL, model engineering / ML Ops, and associated documentation/formatting • Experience working with office productivity software, such as Microsoft Office suite, including Word, Excel, PowerPoint and file sharing applications. • Able to travel, as needed, to meet with government customers and stakeholders • Master’s degree in STEM field, ideally Data Science • Advanced understanding of AI/ML applications in predictive maintenance/logistics • Experience with sensor-based failure predictions and modeling • Experience with Monte-Carlo simulation and calculation of confidence levels
Responsibilities
• Support program initiatives from inception to deployment, ensuring alignment with CBM+ business and mission objectives. • Lead development and deployment of machine learning models, statistical analyses, and data experiments. • Own the analytical framework, ensuring robustness, reproducibility, and scalability. • Partner with domain experts to translate business questions into data-driven insights and products. • Promote and refine standards for experimental design and analysis. • Oversee data collection & processing, including implementation/sustainment of ETL pipelines, as well as cleaning and preprocess datasets for usage • Perform EDA, to include, performing statistical analysis and visualization to understand data patterns, identifying correlations, trends, and insights to drive product development • Lead ML model development using regression, classification, clustering, & deep learning while optimizing models for accuracy, performance, and scalability • Collaborate with a multi-functional team to integrate models into applications or APIs • Continuously monitor deployed models for performance drift and degradation.
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