Senior Data Scientist, Applied ML
Tasks
- Build preprocessing and feature engineering pipelines
- Collaborate with engineering and product teams
- Create feedback loops to improve model accuracy
- Define success criteria for security use cases
- Design model monitoring and evaluation
- Develop, train, and deploy machine learning models
- Document model design tradeoffs and outcomes
- Participate in model and compliance reviews
- Productionize models in cloud environments
- Prototype machine learning approaches
- Validate transform and monitor data pipelines
Perks/Benefits
- 401k employer contribution
- Employer-paid life insurance
- Flexible Remote Friendly Work Options
- Generous paid holidays
- Health Savings Account employer contribution
- Health, dental, vision insurance
- Long-term disability insurance
- Paid time off
- Short-term Disability Insurance
Skills/Tech-stack
AWS | Airflow | Apache Spark | DVC | Data Transformation | Data Validation | Data pipeline | Docker | Entity Extraction | Entity Resolution | Feature Engineering | Language Processing | MLflow | Machine Learning | Model Evaluation | Model Monitoring | Natural Language | Natural Language Processing | Pandas | PyTorch | Python | Scikit-learn | TensorFlow | Text Classification | XGBoost
Education
N/A
Roles
Applied ML Engineer | Data Scientist | Engineer | ML Engineer | Scientist | Senior Data Scientist
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