Data Scientist + AWS @ Iris Software

Required Skills & Qualifications:

- 57 years of industry experience building and deploying machine learning models.

- Strong proficiency with machine learning algorithms including XGBoost, linear regression, and classification models.

- Hands-on experience with AWS SageMaker for model development, training, and deployment.

- Solid programming skills in Python (and relevant libraries such as scikit-learn, pandas, NumPy, etc.).

- Strong understanding of model evaluation metrics, cross-validation, hyperparameter tuning, and performance optimization.

- Experience in working with structured and unstructured datasets.

- Knowledge of best practices in model deployment and monitoring in a production environment (ML Ops desirable).

- Familiarity with tools like Docker, Git, CI/CD pipelines, and AWS ML services.

- Excellent problem-solving skills, critical thinking, and attention to detail.

- Strong communication and collaboration skills.

Nice to Have:

- Experience with additional AWS services like Lambda, S3, Step Functions, CloudWatch.

- Exposure to deep learning frameworks like TensorFlow or PyTorch.

- Familiarity with DataOps practices and agile methodologies.