Overview
Remote Data Scientist role focused on building and optimizing machine learning models for time series forecasting and predictive analytics.
What you'll do
- Develop and optimize machine learning models for time series forecasting and predictive analytics.
- Perform feature engineering and model optimization to improve model accuracy and efficiency.
- Evaluate model performance using metrics including MAPE, RMSE, and R² and adjust strategies.
- Build data pipelines using PySpark, SQL, and cloud-based solutions for data integration.
- Extract, transform, and load data using tools such as Boomi, SnapLogic, SSIS, or Palantir.
- Deploy, monitor, and continuously improve machine learning models in production environments.
What you'll need
- Proficiency in Python, PySpark, and SQL.
- Expertise in time series forecasting models including ARIMA, Prophet, and LSTMs.
- Experience with data model optimization, feature engineering, and performance evaluation.
- Hands-on experience in data engineering (pipelines, ETL, and data transformation).
- Experience using data integration tools such as Boomi, SnapLogic, SSIS, or Palantir.
- Cloud computing experience, particularly Google Cloud services (e.g., BigQuery, Vertex AI).
Nice to have
- Experience with MLOps for continuous deployment, monitoring, and retraining.
- Familiarity with object-oriented programming languages such as C#, Java, or JavaScript.
Details
- Location: Remote (US).
- Salary range: $110,000–$117,000 USD annually.
Read the full description and apply on the company’s own careers page.
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