Data Scientist

Role Overview

Support the development of statistical, Bayesian, and machine learning models to enhance forecasting capabilities and quantify uncertainty to guide decision-making across the company.

What You Will Do

Develop and refine statistical, Bayesian, and machine learning models to support demand forecasting, analyze large, complex datasets, and contribute across the modeling lifecycle.

Why It Might Be a Fit

The position is well suited to a curious and collaborative problem solver who is excited about applying forecasting methods, complex datasets, and modern analytical tools to build decision-support solutions that inform planning and business decision-making.

Requirements

• 4+ years of experience applying data science, analytics, or statistical modeling in industry, research, or enterprise environments.
• Experience with time-series forecasting, predictive modeling, or related quantitative methods.
• Proficiency in Python and SQL, with experience using tools such as scikit-learn, PyMC, PyTorch, TensorFlow, or similar data science libraries.
• Solid analytical and statistical foundation, with the ability to work with messy and complex datasets to generate actionable insights.
• Familiarity with model development workflows, including data preparation, feature engineering, evaluation, and interpretation.
• Strong communication skills, with the ability to explain technical concepts and results to a range of stakeholders.
• Strong collaboration skills and ability to work effectively in cross-functional environments.
• Intellectual curiosity and a willingness to learn, take on ambiguous problems, and grow in a fast-paced environment