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Mid-level ML/Data Scientist title, metro location, and broad generalist skillset increase candidate competition.
Core ML and model-development skills are broadly transferable across industries.
Explicit 4-7 years requirement plus mandatory ML frameworks and production deployment skills strongly filter candidates.
Design and implement predictive and prescriptive models including regression, classification, and optimization using advanced techniques (e.g., XGBoost, LightGBM).
Develop and tune machine learning models with Python, PySpark, TensorFlow, and PyTorch, producing scalable and production-ready code.
Collaborate with stakeholders and cross-functional teams to integrate models into business processes and build monitoring dashboards for model performance.
Bachelor's degree in Computer Science, Engineering, or related field.
4-7 years of experience in Data Science domain.
Experience with predictive modeling techniques and coding in Python, PySpark, TensorFlow, and PyTorch.
Not explicitly mentioned: Notice period or location restrictions beyond California disclosure.
Experienced in building scalable ML models and operationalizing them in production environments.
Able to translate business challenges into technical data science solutions and work cross-functionally.
Comfortable working in Agile development environments with iterative cycles and adapting to changing priorities.