Description

You develop and implement time series forecasting models to predict trends, demand, and performance metrics.

Responsibilities

• Develop and implement time series forecasting models using statistical, machine learning, and deep learning techniques.
• Process, clean, and transform large, multi-source datasets for model ingestion.
• Analyze historical data patterns to identify drivers for future outcomes and perform data validation.
• Collaborate with technical and business teams to align models with forecasting needs.
• Document all processes, models, and code for reproducibility and scalability.

Required Skills

• 6+ years of experience in data science focused on time series forecasting.
• Proficiency in Python or R for data analysis and modeling.
• Strong knowledge of time series techniques (ARIMA, SARIMA, ETS, Prophet, LSTM).
• Experience with machine learning algorithms and statistical analysis.
• Familiarity with SQL, Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Experience working with large datasets and data pipelines in AWS, Azure, or GCP.
• Bachelor's or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or related field.
• Excellent communication skills to translate complex data findings into actionable business insights.

Key Skills

Education

Bachelor's or Master's degrees