Senior Data Scientist
- Posted 6 hours ago
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Job Description
- 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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Key Skills
support vector machines
data pipelines
statistical forecasting models
unsupervised learning algorithms
random forests
recurrent neural networks
convolutional neural networks
deep learning techniques
machine learning models
About Company
Skills:
Data Warehousing, Big Data Technologies, Kafka, Data Modeling, Distributed Systems, Python, AWS, Sql, Devops, Gcp, Spark, Data Governance, Databricks, Azure, Airflow, orchestration tools, CI CD, Security, ETL ELT pipelines, data workflows, infrastructure-as-code, dbt, best practices, cloud data platforms, data engineering frameworks
Skills:
Scipy, Numpy, Neural Networks, Svm, Naive Bayes, Sql, Python, Pandas Library, scikit-learn, decision forests