Senior Data Scientist

• Develop and implement statistical forecasting models to predict future market demand, sales trends, and customer behavior.
• Utilize regression analysis techniques to understand the relationships between various factors and business outcomes.
• Collect, clean, and transform large datasets from various sources, including internal databases, external APIs, and public data repositories.
• Engineer relevant features from raw data to improve model performance and extract meaningful insights.
• Develop and implement data pipelines for efficient data extraction, transformation, and loading (ETL).
• Develop and deploy machine learning models, including supervised and unsupervised learning algorithms (e.g., decision trees, random forests, support vector machines, neural networks).
• Explore and implement deep learning techniques, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks1 (GANs), for complex tasks like image recognition, natural language processing, and time series forecasting.
• Train, validate, and evaluate machine learning models using appropriate metrics and techniques.
• Monitor model performance over time and implement necessary adjustments to maintain accuracy and effectiveness.
• Communicate model findings and insights to stakeholders in a clear and concise manner.
• Experience in HVAC, manufacturing, supply chain, SIOP, engineering, service operations, or related industrial processes.

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