Position Overview

We are seeking a high-level Data Scientist with a heavy emphasis on Operations Research (OR) to join the team. This role is focused on high-impact solutioning, from exploratory data analysis (EDA) and model development to deploying prototypes and Proof of Concepts (POCs) for rapid validation.

The ideal candidate is an expert in mathematical modeling—specifically Linear Programming (LP) and Mixed-Integer Programming (MIP)—to drive network optimization and demand forecasting within a cloud production environment.

Core Responsibilities

Model Development & Testing: Ideate, develop, and train advanced models, including neural networks (DNN, RNN, LSTM) for predictive analytics.
Operations Research: Apply expertise in mathematical modeling and network optimization to solve complex supply chain or business logic problems.
Forecasting & EDA: Conduct deep-dive exploratory data analysis and implement forecasting techniques using Time Series and ARIMA models.
Prototyping & POCs: Create and test prototypes for quick feasibility validation and conduct experiments to quantify business impact.
Cloud Deployment: Deploy and monitor models in cloud production environments (specifically Google Cloud Platform), ensuring ongoing optimization and performance.
Data Visualization: Translate complex data sets into actionable insights using Tableau and Looker Studio.

Technical Requirements

Advanced Mathematics: Strong experience in Linear Programming (LP) and Mixed-Integer Programming (MIP).
Programming & Tools: Proficiency in Python and SQL for backend development and modeling.
Cloud Infrastructure: Experience deploying models on Google Cloud Platform (Google Cloud Platform) or similar cloud environments.
Machine Learning: Deep understanding of Neural Networks and Time Series forecasting.
Version Control: Collaborative development experience using Git.

Data Scientist

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