Data Scientist

Engagement Type: [Full-Time / Contractor]

Key Responsibilities

Develop & Deploy Predictive Machine Learning Models: Design, validate, and deploy production-grade statistical and machine learning models for anomaly detection, cost forecasting, rate modeling, and invoice classification.

Apply Modern NLP & LLM Techniques: Leverage Natural Language Processing (NLP), embeddings, and Large Language Models (LLMs) to extract structured insights from complex, unstructured supply chain documents and logistics contracts.

Build & Productionize Data Pipelines: Partner directly with AI and software engineers to build scalable feature engineering pipelines, model monitoring systems, and automated retraining workflows.

Conduct Advanced Exploratory & Scenario Analysis: Clean and analyze large-scale transactional datasets, designing experimental scenario models to optimize shipping trends, carrier rate comparisons, and contract negotiations.

Translate Data into Business Strategy: Query enterprise databases with advanced SQL, crafting clear data visualizations and executive presentations to translate complex findings into actionable business solutions.

Maintain Governance & Model Performance: Enforce rigorous data quality checks, statistical validations, and security standards across cloud data platforms.

What You Bring

Core Experience: Proven track record in data science, developing end-to-end machine learning models and statistical solutions for complex, high-volume transactional data.

Technical Stack Expertise: Deep proficiency in Python and standard data science libraries (pandas, NumPy, scikit-learn, statsmodels).

Advanced Database & Querying Skills: Expertise in writing complex SQL queries across MS SQL Server and PostgreSQL architectures.

Modeling & AI Specialization: Strong foundation in machine learning techniques (regression, classification, time series forecasting, clustering) combined with hands-on exposure to NLP, embeddings, and LLM techniques.

Cloud & Analytics Tools: Experience using cloud ML platforms (Azure ML Studio / Azure AI Foundry preferred) and data visualization tools (Power BI, Tableau or Python plotting libraries).

Communication & Ownership: Fluent English (written and verbal) with the ability to articulate complex data insights to non-technical business partners and drive analytical initiatives independently.

What You’ll Love

USA Contractor / 100% Remote

Competitive Pay (USD)

Holidays Off & Paid Time Off