Senior Data Scientist
Tasks
- Apply privacy compliant data handling practices
- Build and operate retrieval augmented generation systems
- Build production quality Python and PySpark models
- Define modeling methodology and evaluation frameworks
- Design agentic AI systems for production
- Drive technical design and create solution documentation
- Establish MLOps practices for experiment tracking and monitoring
- Implement model retraining workflows and reproducibility standards
- Integrate large language models into production ML pipelines
- Mentor data scientists through feedback and design reviews
- Orchestrate pipelines with AirFlow
- Own end to end delivery of data science projects
- Partner with data engineering on data requirements
- Translate business requirements into modeling solutions
Perks/Benefits
- Disability insurance
- Health insurance
- Life insurance
- Paid Holidays
- Paid time off
- Retirement savings plan
- Wellness offerings
Skills/Tech-stack
A/B | A/B Testing | Agent Orchestration | Airflow | B testing | CCPA | Causal Inference | Databricks | Delta Lake | Experiment tracking | GDPR | Graph Neural Network | Graph Neural Networks | Knowledge graphs | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Milvus | Model Monitoring | Natural Language | Natural Language Processing | Neural Network | Neural Networks | PGVector | Pinecone | Prompt engineering | PySpark | Python | Reproducible Research | Retrieval-Augmented Generation | SQL | Uplift Modeling | Vector Databases | Weaviate
Education
Roles
Regions
Countries
States
Cities
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