Lead Data Scientist
Tasks
- Apply A B testing frameworks
- Build data pipelines for structured and unstructured data
- Build model evaluation pipelines
- Communicate modeling concepts to stakeholders
- Conduct hypothesis-driven experimentation
- Design machine learning services
- Develop predictive generative and analytical models
- Establish ML AI engineering standards
- Implement model training workflows
- Implement model versioning strategies
- Implement testing strategies for ML systems
- Mentor product engineering teams on AI roadmaps
- Optimize models for performance cost latency
- Perform exploratory data analysis
- Perform feature engineering
- Prototype and evaluate machine learning models
- Set up monitoring observability and reliability
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | API Development | B testing | Data Analysis | Data Pipelines | Data Visualization | Deep learning | Distributed Systems | Exploratory Data Analysis | Feature Engineering | Hypothesis Testing | Jupyter | Machine Learning | Mathematical Optimization | Microservices | Model Explainability | Model Training | Model versioning | NoSQL | Pandas | Plotly | Probability theory | PyTorch | Python | Scikit-learn | Statistical modeling | Tableau | TensorFlow | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Data Scientist | Lead | Lead Data | Lead Data Scientist | Scientist
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