Application Architect III

Location:

Plano, TX

Salary Range:

Competitive

Introduction

We are seeking a highly skilled professional to join our team. This role involves working on advanced machine learning projects, requiring expertise in model development and data science. The ideal candidate will have a strong background in Python and machine learning frameworks, and will be comfortable with data exploration and model deployment.

Required Skills & Qualifications 

• 5–10 years of hands-on data science or machine learning engineering experience delivering models, pipelines, or analytics solutions in highly technical environments.
• Strong Python development experience, including experience with common data science and machine learning libraries such as pandas, NumPy, scikit-learn, XGBoost, or similar frameworks.
• Deep understanding of supervised machine learning classification approaches, including feature engineering, model training, hyperparameter tuning, validation, threshold selection, and model performance evaluation.
• Experience with distributed data processing, cloud platforms, or large-scale analytics environments such as Spark, Databricks, Hadoop, AWS, Azure, or similar technologies.
• Experience developing classification models for fraud, risk, cybersecurity, authentication, customer behavior, anomaly detection, or other high-volume decisioning use cases.

Preferred Skills & Qualifications 

• Familiarity with MLOps practices, including model packaging, version control, automated testing, CI/CD pipelines, model monitoring, and reproducible deployment workflows.
• Prior work experience at client or in client's Industry
• Applicants must be able to work directly for Artech on W2
• Master’s or PhD in a quantitative or technical field such as computer science, statistics, mathematics, engineering, data science, or a related discipline.

Day-to-Day Responsibilities 

• Design, build, train, validate, and tune supervised machine learning classification models using structured, behavioral, and transactional data.
• Perform hands-on data exploration, cleansing, transformation, and feature engineering to create reliable inputs for model development.
• Develop repeatable Python-based workflows, scripts, and pipelines for dataset preparation, model training, evaluation, and scoring.

For immediate consideration please click APPLY to begin the screening process.