Data Scientist

About CodeRoad

About CodeRoad

CodeRoad is a technology execution partner trusted by companies across North America since 2002. We work alongside our clients to engineer, modernize, and scale the technology that powers their businesses, combining deep technical expertise, specialized teams, and shared accountability for outcomes. Our capabilities span product engineering, platform engineering, legacy modernization, and AI engineering.

Our engineers, designers, delivery leaders, and technology specialists collaborate through Velocity Studios: specialized teams developed within CodeRoad to deliver complex technology initiatives. Being assigned to a project means you become part of a collaborative environment where you can strengthen your expertise, take ownership of meaningful work, and grow alongside experienced professionals.

Why Build Your Career at CodeRoad?

• We work close to the technology, teams and roadmaps that move real outcomes. Direct engagement with U.S. client teams and roadmaps
• Your career here can outlast any single project. Continuous multi-project pipeline; long-tenure CodeRoaders.
• We invest in the skills that shape what's next. Agentic AI tools and training, Coursera Enterprise, Studio practice labs, L1-L7 Career Framework.
• You grow in an environment built on trust, transparency and recognition. High-touch onboarding, transparent leadership communication, community recognition, psychological safety.

Responsibilities

• Build, test, and refine machine learning and statistical models to identify anomalies, forecast costs, analyze shipping rates, and classify invoices. Evaluate model performance and contribute to improving predictive accuracy.
• Explore and apply Natural Language Processing (NLP), embeddings, and Large Language Models (LLMs) to extract meaningful insights from unstructured supply chain documents, logistics contracts, and other business data.
• Collaborate with AI and software engineers to prepare datasets, develop feature engineering workflows, and support model deployment, monitoring, and automated retraining.
• Clean, transform, and analyze transactional datasets to identify patterns, evaluate shipping trends, compare carrier rates, and support cost optimization and contract negotiation decisions.
• Use SQL, statistical analysis, and data visualization to communicate findings clearly and turn complex data into actionable recommendations for business stakeholders.
• Implement data quality checks, validate analytical results, monitor model performance, and follow established security and governance standards across cloud data environments.
• Proactively experiment with AI tools, libraries, and techniques to improve analytical workflows, automate repetitive tasks, accelerate experimentation, and identify new ways to solve business problems.

Requirements

• 1–3 years of professional experience in data science, machine learning, applied statistics, or a related analytical role, with hands-on experience working on real-world datasets and analytical projects.
• Practical experience with Python and common data science libraries such as pandas, NumPy, and scikit-learn. Familiarity with statsmodels or similar statistical tools is a plus.
• Experience writing SQL queries to retrieve, transform, and analyze data from relational databases. Familiarity with Microsoft SQL Server or PostgreSQL is preferred.
• A proactive mindset toward exploring and applying AI tools to improve productivity, automate repetitive analytical tasks, accelerate experimentation, and develop creative solutions. Curiosity, initiative, and a willingness to learn and experiment with emerging AI technologies are especially valued.
• Strong problem-solving skills, attention to detail, and the ability to work with complex datasets, validate assumptions, and draw meaningful conclusions. Comfortable taking initiative, learning independently, and collaborating with cross-functional teams.
• Good English communication skills, both written and verbal, with the ability to explain analytical findings and technical concepts clearly to non-technical stakeholders.
• What You’ll Love

Preferred

• A solid understanding of machine learning concepts, including regression, classification, clustering, and time series forecasting. Exposure to NLP, embeddings, and LLMs is highly desirable, particularly through hands-on projects or practical applications.
• Familiarity with cloud-based machine learning or AI platforms, preferably Azure Machine Learning or Azure AI Foundry. Experience with Power BI, Tableau, or Python visualization libraries is an advantage.

Benefits

• USA Contractor / 100% Remote
• Opportunity to work with high-growth US-based companies and cutting-edge tech stacks.
• Ready to Build What Actually Ships?

Engagement Type

[Full-Time / Contractor]

Explore opportunities and

submit your application today!