Data Scientist
RemoteUnited States
United StatesRemoteFull TimeDoctorate Or Professional DegreeStartup
Full TimeDoctorate Or Professional DegreeStartup
Job Summary
Develop anomaly detection models for transformer fault POCs and thermal data projects, scaling existing solutions while integrating forecasting and linear regression techniques. Implement machine learning and deep learning algorithms for prediction, classification, and clustering using Python, PySpark, and neural networks within the Keras/TensorFlow framework. Collaborate with multi-disciplinary teams to evaluate business context and identify predictive caveats, ensuring robust model performance in power and manufacturing environments. Requires proficiency in pandas, scikit-learn, and Linux-based containerization tools like Docker.
Required Qualifications
- Understanding of machine learning and deep learning models to select and implement for prediction, classification, and clustering
- Understanding of the business context of projects and able to identify areas where models will be less predictive or have caveats to their predictive powers
- Ability to communicate and establish good relations with multi-disciplinary teams
- Expertise with neural networks, specifically RNNs within the Keras/TensorFlow framework
- Proficiency with Python, including pandas, scikit-learn
- Experience in PySpark
- Bachelors degree in a quantitative field, such as Statistics, Mathematics, Computer Science, Economics, Engineering, or Operations Research
- 3+ years of experience in statistical modeling and quantitative analysis in industry or full-time academic research
Desired Qualifications
- Advanced Degree (MS or PhD) in Statistics, Mathematics or Quantitative Marketing with a focus on machine learning
- Knowledge of power transformers, experience with electrical engineering
- Prior experience predictive maintenance in a power or manufacturing environment
- Experience with Databricks, AWS SageMaker and/or Google Vertex AI
- Comfortable working in Linux
- Experience with Git
- Experience with Docker containers
- Good communication skills
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