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Popular mid-level data science role in a metro with broad skill requirements, increasing applicant competition.
Specialized forecasting and production ML skills moderate transferability across industries.
Explicit 5+ years plus mandatory forecasting, production ML, and GCP expertise increases shortlisting strictness.
Design, build, and deploy statistical, probabilistic forecasting, and machine learning models for demand, capacity, and trend analysis.
Own the full model lifecycle including development, backtesting, deployment, monitoring, and retraining on Google Cloud Platform (GCP).
Collaborate with cross-functional teams to generate actionable insights and support decision-making through data visualization and stakeholder communication.
5+ years of experience in data science, applied statistics, or machine learning.
Strong expertise in statistics, time series analysis, probabilistic forecasting, and machine learning (regression, boosting, neural networks).
Proficiency in Python, SQL, ML libraries (pandas, NumPy, scikit-learn, statsmodels, PyTorch/TensorFlow), and experience with GCP.
Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or related quantitative field.
Experienced in owning and scaling production-ready forecasting and ML models with end-to-end responsibility including MLOps.
Skilled in handling large, complex datasets and collaborating effectively with data engineering and cross-functional teams.
Strong focus on deploying robust, interpretable forecasting solutions balancing accuracy and operational needs in a cloud environment.