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Metro location, popular generalist data role, and broad skill requirements increase applicant competition.
Data science skills are broadly transferable across industries and roles.
Low explicit experience threshold and basic technical requirements reduce strictness.
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Develop, test, and implement statistical and machine learning models under guidance, ensuring reliability and alignment with objectives.
Execute well-defined analytical tasks including data cleaning, transformation, exploratory data analysis, hypothesis testing, and feature engineering.
Support model validation, experimentation (including GenAI/LLM techniques), documentation, and collaborate closely with senior data scientists and data engineers.
Bachelor’s Degree in Data Science, Statistics, Mathematics, Computer Science, or related field.
0–1 year of experience; fresh graduates encouraged to apply; academic or internship experience in analytics/data science is a plus.
Basic proficiency in Python, R, or similar analytical programming languages.
This role requires 100% in-office work; minimal travel required.
Operates effectively under guidance within structured workflows supporting model development and validation.
Strong focus on accuracy, consistency, and disciplined validation in model outputs and analytics.
Comfortable working in an office setting collaborating with senior data scientists and data engineers, with exposure to advanced analytics including NLP and GenAI techniques.