Decision Intelligence Engineer - Next Best Action
Tasks
- Build nightly Databricks training workflow
- Define feedback loop contracts
- Design reinforcement learning policies
- Detect policy failure modes
- Document model behavior and failure modes
- Enforce constraints in optimization objective
- Engineer features from clinical data
- Evaluate policies with simulation and backtesting
- Implement long horizon sequential decision algorithms
- Implement multi agent decisioning methods
- Integrate outputs with real time decisioning systems
- Manage model artifacts in MLflow Model Registry
- Model problems as Markov decision processes
- Run batch scoring for eligible members
- Support explainability and compliance requirements
- Track experiments with MLflow
- Train policies with distributed reinforcement learning
Perks/Benefits
Skills/Tech-stack
Batch Scoring | Bellman Equation | Constrained MDP | Constrained optimization | Data Lineage | Databricks | Databricks Unity | Databricks Unity Catalog | Decision Processes | Delta Lake | Discrete Event Simulation | Discrete event | Distributed Training | Dynamic Programming | Event simulation) | Experiment tracking | Exploration Exploitation Tradeoff | Exploration/exploitation | Feature Engineering | Graphical Model | Graphical Models | Gymnasium | Integer Programming | Lagrangian Relaxation | MARL | ML experiment tracking | MLflow | Markov Decision Processes | Mixed Integer | Mixed-Integer Programming | Model Registry | Monte Carlo | OpenTelemetry | PettingZoo | Probabilistic Graphical Models | PySpark | PyTorch | Python | Ray RLlib | Reinforcement Learning | Reward shaping | SimPy | Simulation | Stochastic Processes | TensorFlow | Unity Catalog
Education
N/A
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