Role Overview
CodeRoad is a technology execution partner that works alongside clients to engineer, modernize, and scale technology. As a Data Scientist, you’ll develop predictive machine learning models, apply modern NLP and LLM techniques, and build data pipelines. You’ll work in a collaborative environment with experienced professionals, strengthening your expertise and taking ownership of meaningful work.
What You Will Do
Your key responsibilities will include developing and deploying predictive machine learning models, applying modern NLP and LLM techniques, building and productionizing data pipelines, conducting advanced exploratory and scenario analysis, and translating data into business strategy.
Why It Might Be a Fit
You’ll love working 100% remote, with competitive pay, holidays off, paid time off, and health insurance assistance. You’ll have the opportunity to work with high-growth US-based companies and cutting-edge tech stacks.
Requirements
- Proven track record in data science
- Developing end-to-end machine learning models and statistical solutions for complex, high-volume transactional data
- Deep proficiency in Python and standard data science libraries (pandas, NumPy, scikit-learn, statsmodels)
- Expertise in writing complex SQL queries across MS SQL Server and PostgreSQL architectures
- Strong foundation in machine learning techniques (regression, classification, time series forecasting, clustering) combined with hands-on exposure to NLP, embeddings, and LLM techniques
- Experience using cloud ML platforms (Azure ML Studio / Azure AI Foundry preferred) and data visualization tools (Power BI, Tableau or Python plotting libraries)
- Fluent English (written and verbal) with the ability to articulate complex data insights to non-technical business partners
Benefits
- Competitive pay (USD)
- Holidays off
- Paid time off
- Health insurance assistance program
- Opportunity to work with high-growth US-based companies and cutting-edge tech stacks
To apply for this job please visit job-boards.greenhouse.io.

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