Description
You will design and develop machine learning models to solve complex business problems using multilayered datasets.
Responsibilities
- Experiment with various models, evaluating performance and conducting model selection.
- Perform data cleaning, feature engineering, and feature selection.
- Implement data and model training pipelines on AWS using SageMaker and Lambda functions.
- Document model architectures and technical solutions.
- Collaborate with platform engineers, data engineers, and software developers to meet business requirements.
Required Skills
- 3+ years of experience with Python, SQL, and Statistics.
- Deep learning experience using PyTorch or TensorFlow.
- Proficiency in advanced mathematics, including calculus, linear algebra, functional analysis, and Bayesian statistics.
- Experience with time series forecasting using Prophet or Elastin.
- Practical knowledge of predictive modeling for classification, clustering, and forecasting.
- Experience with object-oriented programming and the software development lifecycle.
- Exposure to deploying and monitoring models in production.
- Hands-on experience with version control systems like GitHub or CodeCommit.
- Exposure to Docker containerization.
- Technical experience developing and implementing cloud ML models on AWS.
Preferred Skills
- Experience with ensemble machine learning models.
- Familiarity with AWS services including ECS, Airflow, and Elasticsearch.
- Knowledge of DevOps practices and CI/CD pipelines for data solutions.