Senior Data Scientist – Machine Learning

HeartCentrix Solutions; Town of Texas (WI); On-site; USD 120,000 - 170,000; Full time

Job summary

HeartCentrix Solutions seeks a hands-on Data Scientist/ML Engineer to join a centralized ML team supporting multiple business units. This role focuses on taking models and pipelines from development into production, with an emphasis on scalable, reliable systems.

You will write production-grade Python, refactor legacy code, optimize ML pipelines, and collaborate with data scientists and engineers to deploy and monitor ML solutions in cloud environments.

Qualifications

• MS or PhD in a quantitative field.
• Strong Python programming and debugging skills.
• Hands-on experience deploying ML models to production.
• Experience with scalable ML pipelines.

Responsibilities

• Build, improve, and productionize machine learning pipelines and models.
• Take ML solutions from prototype through deployment, monitoring, and optimization.
• Write clean, production-quality Python code with modularity and testing.
• Refactor and improve existing codebases alongside new models.
• Collaborate with data scientists and data engineers to scale solutions.
• Support data extraction, cleaning, analysis, and feature engineering.
• Design and optimize ML workflows, including orchestration and monitoring.
• Work with large datasets and cloud-based technologies to scale development.

Skills

Python

ML pipeline experience

Production-grade coding

Education

MS or PhD in Data Science, Computer Science, Statistics, ML, Applied Mathematics, or related quantitative field

Tools

Databricks

Spark

MLflow

CI/CD

Azure

Tableau

Power BI

Job description

We're looking for a hands-on Data Scientist/Machine Learning Engineer to join a centralized ML team supporting multiple business units. This person will focus heavily on taking machine learning models and pipelines from development into production.

This is a great fit for someone who enjoys working with Python, improving existing code, optimizing ML systems, and making sure models are scalable, reliable, and production-ready.

What You'll Be Doing

• Build, improve, and productionize machine learning pipelines and models
• Take ML solutions from prototype through deployment, monitoring, and optimization
• Write clean, production-quality Python code with a focus on modularity, testing, debugging, and performance
• Refactor and improve existing codebases rather than only building new models
• Work with data scientists and data engineers to turn ML concepts into scalable production solutions
• Support data extraction, cleaning, analysis, and feature engineering
• Help design and optimize ML workflows, including orchestration and monitoring
• Work with large datasets and cloud-based technologies to scale ML development and deployment
• Troubleshoot technical issues and identify opportunities to improve performance and reliability
• Communicate effectively with technical and business partners across the organization

Top 3 Must-Haves

• MS or PhD in Data Science, Computer Science, Statistics, Machine Learning, Applied Mathematics, or a related quantitative field
• Strong Python expertise - production-grade coding, modularization, testing, debugging, and performance tuning
• Hands-on machine learning pipeline experience - including model deployment, orchestration, monitoring, and optimization

Nice-to-Haves

• Experience with Databricks and/or Spark-based ML pipelines
• Strong SQL skills and experience working with large-scale datasets
• Experience with ML lifecycle tools such as MLflow, CI/CD, and model monitoring
• Experience with Azure or other cloud platforms
• Experience with parallel processing and scalable ML environments
• Experience with data visualization tools such as Tableau or Power BI