Data Scientist

Job not on LinkedIn

🔥 14 hours ago

💃 Latin America – Remote

⏰ Full Time

🟢 Junior

📊 Data Scientist

🚫👨‍🎓 No degree required

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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CodeRoad

WebsiteLinkedInAll Job Openings

1 - 10 employees

📚 Education

☁️ SaaS

Education • SaaS

CodeRoad is a comprehensive online training program that teaches JavaScript and front-end web development from zero to a Junior Front-End Developer level. Created and taught by Mateusz Choma, the course includes 175+ hours of video lessons, hands-on code examples in an in-browser editor, and covers HTML, CSS, JavaScript, React and Redux, plus community Q&A and optional one-on-one mentoring. The platform is self-paced and accessible 24/7, aimed at individuals seeking to start a career in front-end development.

📋 Description

• 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 • Apply NLP, embeddings, and LLMs to extract insights from unstructured supply chain documents, logistics contracts, and business data • Prepare datasets and develop feature engineering workflows • Support model deployment, monitoring, and automated retraining • Clean, transform, and analyze transactional datasets • 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 and provide actionable recommendations • Implement data quality checks and validate analytical results • Monitor model performance and follow security and governance standards across cloud data environments • Experiment with AI tools, libraries, and techniques to improve analytical workflows and automate repetitive tasks • Collaborate with AI and software engineers and cross-functional teams

🎯 Requirements

• 1–3 years of professional experience in data science, machine learning, applied statistics, or a related analytical role • 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 • 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 • Proactive mindset toward exploring and applying AI tools • Strong problem-solving skills and attention to detail • 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 • Ability to explain analytical findings and technical concepts clearly to non-technical stakeholders

🏖️ Benefits

• USA Contractor / 100% Remote • 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. • Agentic AI tools and training • Coursera Enterprise • Studio practice labs • High-touch onboarding • Transparent leadership communication • Community recognition • Psychological safety

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