Back
Tier-1 brand, mid-level popular data role, metro location, and broad skill requirements increase competition.
Forecasting and probabilistic modeling skills are transferable, but domain knowledge adds moderate sensitivity.
Explicit 2+ years plus required ML/forecasting tools create moderate hiring filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and refine statistical, Bayesian, and machine learning models to support demand forecasting across various planning horizons.
Analyze large and complex datasets to generate actionable insights that guide business decision-making.
Contribute to the full modeling lifecycle including business problem framing, feature engineering, model development, validation, deployment support, monitoring, and explainability.
2+ years of experience applying data science, analytics, or statistical modeling in industry, research, or enterprise environments.
Experience with time-series forecasting, predictive modeling, or related quantitative methods.
Proficiency in Python and SQL with experience in libraries such as scikit-learn, PyMC, PyTorch, or TensorFlow.
Strong analytical and statistical foundation with ability to handle complex datasets.
Experience working cross-functionally to build forecasting solutions that support business decision-making.
Familiarity with model development workflows including data preparation, feature engineering, evaluation, and interpretation.
Ability to clearly communicate analytical findings to both technical and non-technical stakeholders and collaborate effectively in a team setting.