Data Scientist: ML in Production & Business Impact

Evlo AI; Raleigh (NC); On-site; USD 120,000 - 160,000; Full time

Job summary

Evlo AI is seeking a data scientist to own end‑to‑end data science lifecycle, turning complex datasets into scalable predictive models and actionable insights. You will work with data engineers and product stakeholders to deliver measurable impact with reliable production models.

The role requires 3–6 years in data science, strong Python/SQL skills, and experience deploying models in cloud environments. A quantitative degree is expected; bonus for LLM integrations and MLflow experience.

Qualifications

• 3–6 years of data science or quantitative ML experience.
• Strong Python/SQL with ML libraries.
• Production model deployment in cloud environments.
• Solid stats, experimental design, hypothesis testing.
• Bachelor’s or Master’s in a quantitative field.
• Bonus: LLM integrations, MLflow, or peer-reviewed research publications.

Responsibilities

• Develop and deploy ML models and analytics pipelines.
• Perform exploratory data analysis and feature engineering using Python, SQL, and distributed computing like PySpark.
• Collaborate with data engineers to prepare data for training and inference.
• Evaluate models with metrics, run A/B tests, and improve accuracy.
• Communicate findings clearly to cross‑functional stakeholders and leadership.
• Contribute to internal tooling and code quality via peer reviews and documentation.

Skills

Python

SQL

Statistical modeling

A/B testing

Communication

Collaboration

Education

Bachelor’s or Master’s in Statistics/Computer Science/Mathematics/Economics

Tools

scikit-learn

pandas

NumPy

PyTorch/TensorFlow

MLflow

AWS/GCP/Azure

Job description

Evlo AI is seeking a data scientist to own end‑to‑end data science lifecycle, turning complex datasets into scalable predictive models and actionable insights. You will work with data engineers and product stakeholders to deliver measurable impact with reliable production models.

The role requires 3–6 years in data science, strong Python/SQL skills, and experience deploying models in cloud environments. A quantitative degree is expected; bonus for LLM integrations and MLflow experience.