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Entry-level, popular data science role with broad ML/AI skills and hybrid metro setting drives high applicant density.
Core Python, SQL, statistics and ML skills are highly transferable across industries.
Explicit 0-2 years plus mandatory Python/ML/SQL fundamentals implies moderate technical filtering.
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Perform exploratory data analysis, feature engineering, and build predictive/statistical models using machine learning techniques.
Design and analyze experiments/A-B tests and develop dashboards to measure KPIs and model performance.
Collaborate cross-functionally to translate business questions into data insights, support Generative AI use cases, and operationalize models.
Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or related field.
0-2 years of experience in Data Science, Analytics, Machine Learning, or related areas.
Strong programming skills in Python and working knowledge of SQL.
Solid understanding of statistics, probability, core machine learning concepts, and data manipulation tools like Pandas and NumPy.
Comfortable working on both structured and unstructured data and using statistical methods for modeling and experimentation.
Experience or exposure to Generative AI, A-B testing, and cloud platforms such as Azure, AWS, or Google Cloud is advantageous.
Able to collaborate with engineering and business teams to operationalize analytics and contribute to enterprise-scale AI initiatives.