Sr. Principal Data Scientist / Machine Learning Engineer
Tasks
- Architect production ready DS ML models
- Build automation with ML
- Communicate model results and recommendations
- Define AI/ML technical strategy
- Deploy and monitor models
- Develop and validate DS ML solutions
- Develop optimization models
- Develop pattern recognition models
- Develop predictive analytics models
- Drive MLOps lifecycle management
- Facilitate workshops and discovery sessions
- Gather requirements and explore data
- Identify prioritize and execute AI ML use cases
- Lead AI/ML projects
- Manage project scope, timelines, and deliverables
- Mentor data scientists and ML engineers
- Present progress reports to stakeholders
- Translate business problems into DS ML problems
Perks/Benefits
- N/A
Skills/Tech-stack
AWS SageMaker | Anomaly Detection | Azure Machine Learning | Computer Vision | Data Lakes | Data Processing | Data Warehousing | Deep learning | Distributed Computing | Experimental Design | Hypothesis Testing | Keras | Language Processing | MLOps | Machine Learning | Model Monitoring | NLP | Natural Language | Natural Language Processing | NumPy | Pandas | Predictive Analytics | PyTorch | Python | R | Real Time | Real-time Data | Real-time Data Processing | Reinforcement Learning | Risk Assessment | SQL | Scikit-learn | Series analysis | Spark | Streaming Analytics | Supervised Learning | TensorFlow | Time Series | Time Series Analysis | Unsupervised Learning
Education
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