Data Scientist

Role overview Use data science and machine learning to improve decisions in supply chain and logistics operations. The work includes analyzing transaction and document data, building models for costs, rates, anomalies, and invoice classification, and translating results into practical recommendations for business stakeholders.

Responsibilities - Develop and evaluate statistical and machine learning models for anomaly detection, cost forecasting, shipping-rate analysis, and invoice classification. - Apply NLP, embeddings, and large language models to extract information from contracts, logistics documents, and other unstructured data. - Prepare datasets and build feature workflows with AI and software engineers; support deployment, monitoring, and retraining. - Analyze transaction data and shipping trends to compare carriers and inform cost optimization and contract negotiations. - Use SQL, statistical methods, and visualizations to explain findings and recommend actions. - Validate data and analytical results, monitor model quality, and follow cloud data security and governance practices.

Requirements - One to three years of professional experience in data science, machine learning, applied statistics, or a related analytical role. - Practical Python skills with tools such as pandas, NumPy, and scikit-learn. - Ability to write SQL queries and work with relational databases. - Understanding of regression, classification, clustering, and time-series forecasting. - Strong problem-solving, attention to detail, and ability to explain technical findings clearly in English to non-technical audiences. - Initiative, curiosity, and ability to learn independently while collaborating across teams.

Nice to have - Familiarity with statsmodels, SQL Server, or PostgreSQL. - Practical exposure to NLP, embeddings, or LLMs. - Experience with Azure Machine Learning, Azure AI Foundry, Power BI, Tableau, or Python visualization tools.

Benefits and work setup This is a fully remote US contractor position. The listing includes USD compensation, paid time off and holidays, health insurance assistance, and opportunities to work with US-based companies.