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Mid-level generalist ML role, metro location and broad skillset increase candidate competition.
Strong statistical degree requirement and production ML/cloud experience limit transferability across unrelated industries.
Explicit 4+ years, Statistics degree requirement, and mandatory Python/cloud/ML stack create strict screening filters.
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Own and deliver end-to-end data science projects including problem definition, model development, deployment, and monitoring.
Apply advanced statistical methods and machine learning algorithms on large, complex datasets to generate insights and predictive models.
Develop automated, scalable data analysis and model pipelines leveraging cloud infrastructure and create data visualizations to communicate findings effectively.
4+ years professional experience as Data Scientist, Machine Learning Engineer, or similar role delivering data science projects.
Bachelor's or Master's degree in Statistics or closely related quantitative field with strong statistical foundation.
Proficiency in Python and related data science libraries; hands-on experience with cloud platforms (AWS, Azure, or GCP) for data processing and deployment.
Experience with machine learning techniques (regression, classification, clustering, tree-based models) and data visualization/dashboard creation.
Experienced in managing full data science project lifecycle, including deployment and monitoring in production environments.
Strong statistical background with ability to apply experimental design, hypothesis testing, and inference to real-world business problems.
Familiarity with cloud services (especially GCP), advanced dashboarding tools, and automotive domain knowledge is a plus but not mandatory.