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Applied Data Scientist / Machine Learning Engineer Decision Intelligence - WorkWave
Data Scientist
Drive end‑to‑end ML product development, from problem definition to production deployment, using Python, AWS, and data engineering to deliver scalable, explainable models that directly impact customer decision‑making.
About the role
Key Responsibilities
- Own the full ML lifecycle: define problems, engineer features, train models, and deploy them into production environments.
- Collaborate with product, engineering, and data teams to translate business needs into actionable ML solutions.
- Implement robust monitoring, A/B testing, and performance measurement to ensure models remain accurate and valuable over time.
- Design and maintain scalable data pipelines and model serving infrastructure on AWS.
- Communicate model insights, trade‑offs, and limitations to non‑technical stakeholders, ensuring transparency and trust.
Requirements
- Strong experience with Python, scikit‑learn, TensorFlow/PyTorch, and model deployment tools.
- Proficiency in AWS services (SageMaker, Lambda, ECS, S3) and CI/CD for ML workflows.
- Hands‑on knowledge of data engineering, feature stores, and large‑scale data processing.
- Ability to build explainable, measurable, and production‑ready models that drive business outcomes.
- Excellent communication skills and a product‑mindset.
Skills
pythonmachine learningaws