Data Scientist

Role Overview

Senior Data Scientist designing and implementing advanced optimization and analytics systems for cross-domain manufacturing analytics.

Responsibilities

• Develop and maintain Python-based optimization models for:
  • demand elasticity
  • production planning
  • constraint-based decision systems
• Translate complex business problems into structured analytical and optimization frameworks.
• Build and maintain data pipelines integrating heterogeneous enterprise sources using:
  • BigQuery, GCS, and Python
• Perform data reconciliation, fuzzy matching, and standardization to improve data quality and analytical integrity.
• Create lightweight internal business tools (e.g., Dash or Streamlit) to operationalize analytics.
• Contribute to containerized deployments to enable scalable, maintainable delivery of decision tools.
• Partner with cross-functional stakeholders to define requirements and validate outputs.
• Support semantic alignment across systems via feature definition consistency, cross-system mapping, and ontology-informed modeling.
• Document modeling assumptions, data transformations, and system dependencies for reproducibility and reuse.
• Continuously improve model performance, data quality, and deployment efficiency.

Requirements

• Bachelor’s degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research, or equivalent.
• 3+ years building analytical or optimization models in Python.
• Experience building and maintaining data pipelines using SQL and cloud platforms (e.g., BigQuery, GCS).
• Strong Python proficiency for analysis/modeling (e.g., pandas, NumPy, Pyomo or similar optimization libraries).
• Experience integrating and standardizing heterogeneous enterprise datasets.
• Familiarity with containerization (e.g., Docker) and deploying lightweight cloud applications/services.
• Ability to translate business problems into structured analytical frameworks.
• Strong written and verbal communication; comfortable working cross-functionally.

Nice-to-Haves

• Experience with semantically aligned data structures, ontology-informed modeling, and entity/relationship modeling approaches.