Requirement details:
Role- Data Science Architect Warehouse Intelligence Platform
Location: Cincinnati, OH (Onsite)
Contract: 12+ Months
Job Description:
Master s in Data Science, Computer Science, Industrial Engineering, Operations Research, etc.
7+ years in applied data science with production AI and ML
Strong Python (pandas, Pytorch/ TensorFlow, scikit-learn), SQL, experience with experimentation and statistical inference.
Ability to work with event-driven data (timestamps, state transitions, logs).
Self-starter with the ability to investigate and understand business requirements, translate them into technical specifications, and implement the required design.
Excellent problem-solving and analytical skills. Strong communication and collaboration skills.
Demonstrated experience with production classification, forecasting, and anomaly detection algorithms (e.g., XGBoost, Random Forest, ARIMA/Prophet, LSTM, Isolation Forest) - not just familiarity with LLM-based tools.
Familiarity with operational data sources including PLC/SCADA systems, historian databases, WES/WMS/WCS event logs, and sensor streams as inputs to ML pipelines.
Use-case-first mindset: demonstrated ability to define a specific prediction target and identify required data before building infrastructure. Candidates who default to build the platform first are not the right fit for this role.
Other Requirements/Comments
Familiarity with LLM orchestration, prompt engineering, and RAG (Retrieval-Augmented Generation) for operational intelligence use cases is a plus; primary focus of this role is operational ML, not generative AI.
Experience with warehouse/fulfillment systems: WES/WMS/TMS, automation, labor management.
Azure/Databricks experience: Databricks ML, Delta Lake, MLflow, feature engineering at scale.
Experience deploying models into product workflows (API scoring, batch scoring, streaming signals).
Strong background in Operations Research (OR), Linear Programming, or Reinforcement Learning
Never miss an opportunity! Create an alert based on the job you applied for.
