Job Responsibilities
- Ideate, propose, and deploy machine learning projects for electric, water, and/or gas resource consumption, savings, anomaly detection, time series classification, and other sustainability initiatives.
- Support time-sensitive questions and analyses from internal teams on product performance, trends, and anomalies.
- Support internal initiatives to identify and implement process improvements and automation within data collection, analysis, and machine learning workflows.
- Implement data pipelines to collect, clean, and preprocess data from various sources, ensuring data quality and integrity.
- Communicate findings and insights to technical, non-technical, and senior stakeholders through clear visualizations, reports, and presentations.
- Acquire and apply domain knowledge of Redaptive’s products and software stack to identify and drive the resolution of data inconsistencies, improve model performance, and influence product strategy.
Job Requirements
- Proficiency writing readable, testable, and maintainable Python code and working within Python's data ecosystem (Jupyter, NumPy, Pandas, etc.)
- Deep expertise with querying relational databases (SQL), non-relational databases (NoSQL), and RESTful APIs
- Proficiency building and validating predictive models within the Python ecosystem (scikit-learn, XGBoost, TensorFlow, PyTorch, etc.).
- Ability to take data science and machine learning solutions into a production environment, deploying models (ideally on cloud architecture like AWS, Azure, or GCP), integrating with software systems, retraining and maintenance of production models
- Ability to collaborate through a version control system (Git, GitHub, GitLab, etc.)
- Self-starter able to thrive in a startup environment and work with a high degree of autonomy and positive mindset
- Excellent storytelling skills including the ability to tailor and deliver presentations on complex data analyses to both technical and non-technical audiences
- Strong communication skills and presentation skills
- Tendency towards curiosity and experimentation with a strong attention to detail and business sense
Education and Experience
- Bachelor’s degree (or higher) in statistics, economics, STEM, or similarly quantitative field
- 3+ years of professional data science experience
- Experience working with IoT time-series data
- Experience with infrastructure as code (terraform) and CI/CD platforms (circleCI, travisCI) is a plus
- Experience working with building efficiency, HVAC systems, and/or energy, water, and gas resources is a plus
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