Live opening · Posted 2 days ago
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About the role
Description supplied by the original job listing.
Responsibilities:
Forecast the Future: Design, implement, and optimize machine learning models tailored to Time Series data, including ARIMA, LSTMs, and Transformers.
Model the Trends: Work with regression models (linear, ridge, lasso, polynomial, etc. ) to analyze and predict trends, behaviors, and business outcomes.
Data Wrangling Wizardry: Clean, preprocess, and structure Time Series and tabular data for modeling and analysis.
Experiment and Research: Explore advanced algorithms and hybrid approaches to combine.
Time Series models with regression techniques. Optimize for Scale: Develop scalable and production-ready solutions that integrate seamlessly into real-world supply chain systems.
Collaborate and Innovate: Work closely with cross-functional teams, including product managers, data engineers, and other researchers, to align technical solutions with business needs.
Stay on the Cutting Edge: Keep up with the latest advancements in machine learning, Time Series analysis, and regression modeling to keep our solutions ahead of the curve.
Requirements:
Time Series Expertise: Deep understanding of Time Series analysis, including forecasting, feature engineering, and anomaly detection.
Regression Know-How: Strong experience building and optimizing regression models such as linear, ridge, lasso, polynomial, and logistic regression.
ML Mastery: Hands-on experience with ML frameworks and libraries like TensorFlow, PyTorch, Scikit-learn, and XGBoost.
Data Wizardry: Proficiency in Python and experience working with libraries like Pandas, NumPy, and statsmodels.
Visualization Ninja: Ability to visualize trends, forecasts, and patterns using tools like Matplotlib, Plotly, or Seaborn.
Mathematical Rigor: Strong foundation in statistics, probability, and optimization.
Cloud Savvy: Experience deploying ML models on platforms like AWS, GCP, or Azure.
Bonus Points: Experience with hybrid models (e. g., combining Time Series with regression techniques), Reinforcement Learning, or real-time ML systems.
Experience
2-5 yrs
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