Data Scientist, Enterprise Operations

Description -

Role Summary

The Data Scientist in Supply Chain Planning team is responsible for hands-on development of scenario models, simulations, optimization routines, and decision logic. This role operationalizes the Principal’s architecture into scalable tools and automated pipelines. Collaborates deeply with planners and finance leads.

Key Responsibilities

• Develop and maintain scenario simulation modules (Monte Carlo, probabilistic lead time, demand shocks, capacity constraints).

• Implement optimization models (e.g., ideal SL curves, cost-to-serve models, constrained supply allocations).

• Build interpretable scenario outputs: forecast cones, shock sensitivity charts, risk heatmaps, buffer recommendations.

• Own data pipelines and modeling layers supporting scenario execution.

• Lead cross-regional analyses: risk exposure, scenario stress testing, velocity shifts, cannibalization, aging demand.

• Translate business questions into structured scenario experiments.

• Validate model accuracy, explainability, and alignment to enterprise planning logic.

• Mentor Specialist-level DS and partner with planners on scenario consumption.

• Drive continuous improvement—instrumentation, automation, reliability.

Required Skills & Experience

• 10+ years in Data Science, Modeling, Optimization, or Simulation.

• Strong Python modeling capability (NumPy, Pandas, statsmodels/Prophet/PyTorch optional).

• Hands-on experience with simulation (stochastic/empirical), discrete-event modeling, or time-series stress testing.

• Working knowledge of optimization solvers (e.g., Gurobi, OR-Tools, Pyomo).

• Ability to translate scenario outputs into decision-ready actions for supply/demand/finance teams.

• Solid understanding of IBP/S&OP workflows, planning constraints, and parameter logic (MOQ, SS, ROP, capacity).

• Ability to communicate complex models simply and effectively.

Preferred Experience

• Experience connecting scenario models into planning systems (IBP, APS, SAP, custom Python).

• Familiarity with LLM-assisted analysis and agent-driven simulation orchestration.

• Prior leadership of scenario war rooms or supply chain risk reviews.

Job -

Data & Information Technology

Schedule -

Full time

Shift -

No shift premium (Taiwan)

Travel -

Relocation -

Equal Opportunity Employer (EEO) - 

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

For more information, review HP’s EEO Policy or read about your rights as an applicant under the law here: “Know Your Rights: Workplace Discrimination is Illegal"