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# Data Scientist II

- **Company:** Expert Technology Services
- **Location:** Phoenix, AZ, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Continuous Integration, Data Mining, Data Visualization, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Power BI, Tensorflow, Sql Optimization, Pytorch, Scikit Learn, Information Technology, Xgboost, Machine Learning Operations, Tools for Reporting, Unsupervised Learning
- **Published:** October 9, 2026
- **Apply:** https://www.careerjet.com/jobad/us9b720bb89830b4dfbe12a1df22e370e1

## About the Role

Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or related quantitative field.

 - 3-4 years of experience in data science, machine learning, or predictive analytics roles.
 - Hands-on experience building and validating machine learning models using Python.
 - Strong knowledge of supervised and unsupervised learning techniques.
 - Proficient in statistical analysis, predictive modeling, and data mining methodologies.
 - Advanced SQL skills; experience working with large datasets.
 - Experience with visualization and reporting tools (e.g., Power BI).
 - Excellent communication skills, with the ability to translate technical findings into business recommendations.
Preferred Qualifications:

 - Master's degree in a quantitative discipline.
 - Experience with AWS, Azure, or other cloud-based environments.
 - Familiarity with MLOps, including model deployment, monitoring, CI/CD, and lifecycle management.
 - Experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch, XGBoost).
 - Knowledge of predictive analytics, forecasting, optimization, customer analytics, or operational analytics use cases.

## Description

Develop, test, and optimize machine learning models to address business challenges and provide actionable insights.

 - Perform statistical analyses, forecasting, hypothesis testing, and predictive modeling on large, complex datasets.
 - Collaborate with business stakeholders to identify opportunities for data science to improve decision-making and operational efficiency.
 - Conduct exploratory data analysis to uncover patterns, trends, and business opportunities.
 - Design and evaluate experiments to support strategic initiatives.
 - Build and maintain analytical datasets, reports, dashboards, and data visualizations.
 - Present findings and recommendations to both technical and non-technical audiences.
 - Support the deployment, monitoring, and performance measurement of models in production environments.
 - Work closely with data engineers, analysts, and technology teams throughout the data science lifecycle.
 - Stay updated on emerging machine learning and AI techniques, recommending relevant applications.