Applied Data Scientist / Machine Learning Engineer (Decision Intelligence)
Tasks
- Build feedback loops with product teams
- Communicate ML capabilities and limitations
- Define offline and online evaluation strategies
- Design data and feature pipelines
- Develop and deploy machine learning models
- Drive end to end machine learning ownership
- Implement MLOps model versioning and orchestration
- Integrate machine learning into product workflows
- Make practical trade offs for model and product impact
- Manage cloud data infrastructure for models
- Mentor data scientists and cross functional partners
- Monitor model performance and data drift
- Operate model monitoring and reliability systems
- Prototyping from prototype to production
- Run A B tests and causal measurement
Perks/Benefits
- 401k matching
- Employee assistance program
- Flexible time off
- Flexible work arrangement
- Paid Holidays
- Paid bonding leave
- Paid counseling
- Tuition reimbursement
- Virtual medical care
Skills/Tech-stack
A/B | A/B Testing | AWS | Airflow | Amazon Redshift | Azure | B testing | BigQuery | Causal Inference | DBT | Dagster | Data Drift | Data Drift Detection | Databricks | Drift Detection | Feature Pipelines | Forecasting | GCP | LLMs | MLOps | Machine Learning | Model Monitoring | Model versioning | Optimization | PyTorch | Python | Ranking | Recommendation Systems | SQL | Scikit-learn | Snowflake | Statistical modeling | Supervised Learning | TensorFlow | XGBoost
Education
N/A
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