Data Scientist

Yochana; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Yochana IT Solutions Inc. seeks a senior ML/DS professional to design, deploy, and support production-grade machine learning and analytics solutions.

You will build scalable data pipelines, collaborate across Data Science, Engineering, IT, and Security, and ensure robust operations, monitoring, and governance. The ideal candidate has 5+ years of relevant experience, strong Python/SQL skills, and hands-on cloud platform experience (Azure/Snowflake).

Qualifications

• Bachelor’s degree in Data Science, Machine Learning, Statistics, Computer Science, Software Engineering, or a related field, or equivalent relevant professional experience.
• Five or more years of relevant technical experience, including at least two years deploying or supporting machine learning or advanced analytics solutions in production.
• Strong proficiency in Python and SQL, including the ability to design, review, debug, test, and improve production-quality code.
• Experience with Git-based source control, collaborative code review, automated testing, continuous integration, and release-management practices.
• Experience building or supporting automated pipelines for data processing, model training, model deployment, batch scoring, retraining, or related production workflows.
• Experience implementing solutions on Azure, Snowflake, or comparable cloud and cloud-data platforms, with the ability to become productive across the Medica technology environment.
• Understanding of software packaging, dependency management, environment configuration, artifact versioning, and reproducible development practices.
• Experience implementing or supporting logging, monitoring, alerting, and production troubleshooting capabilities.
• Ability to diagnose issues across model behavior, code, data, pipelines, infrastructure, permissions, and platform services.
• Experience writing clear technical documentation, deployment instructions, architecture guidance, and operational runbooks.
• Ability to communicate technical concepts clearly and collaborate effectively across Data Science, Engineering, IT, Security, platform, and business teams.

Skills

ML lifecycle design

Cross-functional collaboration

Delivery speed vs reliability

Root-cause analysis

Reusable tools & docs

Independent work across teams

Strong written & verbal communication

Ownership & knowledge sharing

Education

Bachelor’s degree in Data Science/ML/Statistics/CS/SE

Master’s degree in Data Science/ML/CS/Statistics/SE (preferred)

Tools

Git

CI/CD

Azure

Snowflake

Containerization

Kubernetes

IaC / Terraform

Model registries

Experiment tracking

Job description

• Bachelor’s degree in Data Science, Machine Learning, Statistics, Computer Science, Software Engineering, or a related field, or equivalent relevant professional experience.
• Five or more years of relevant technical experience, including at least two years deploying or supporting machine learning or advanced analytics solutions in production.
• Strong proficiency in Python and SQL, including the ability to design, review, debug, test, and improve production-quality code.
• Experience with Git-based source control, collaborative code review, automated testing, continuous integration, and release-management practices.
• Experience building or supporting automated pipelines for data processing, model training, model deployment, batch scoring, retraining, or related production workflows.
• Experience implementing solutions on Azure, Snowflake, or comparable cloud and cloud-data platforms, with the ability to become productive across the Medica technology environment.
• Understanding of software packaging, dependency management, environment configuration, artifact versioning, and reproducible development practices.
• Experience implementing or supporting logging, monitoring, alerting, and production troubleshooting capabilities.
• Ability to diagnose issues across model behavior, code, data, pipelines, infrastructure, permissions, and platform services.
• Experience writing clear technical documentation, deployment instructions, architecture guidance, and operational runbooks.
• Ability to communicate technical concepts clearly and collaborate effectively across Data Science, Engineering, IT, Security, platform, and business teams.

Preferred Qualifications

• Master’s degree in Data Science, Computer Science, Machine Learning, Statistics, Software Engineering, or a related discipline.
• Direct experience implementing MLOps solutions with Azure and Snowflake.
• Experience with model registries, experiment tracking, feature management, model-monitoring platforms, or managed machine learning services.
• Experience with containerization, infrastructure as code, workflow orchestration, cloud-native deployment, or platform-engineering practices.
• Experience implementing secure credential management, role-based access controls, auditability, and data-protection controls.
• Experience with model governance, validation, responsible AI practices, or regulated production environments.
• Experience working with healthcare data, including claims, clinical, member, provider, or operational datasets.

Core Skills and Abilities

• Strong software engineering and systems-thinking skills.
• Ability to design solutions across the complete machine learning lifecycle rather than optimizing a single component in isolation.
• Ability to balance delivery speed with reliability, security, maintainability, and governance.
• Strong problem-solving and root-cause-analysis capabilities.
• Ability to translate recurring technical needs into reusable tools, patterns, and documentation.
• Ability to work independently while coordinating effectively across multiple technical and business teams.
• Strong written and verbal communication skills.
• Commitment to continuous improvement, operational ownership, and knowledge sharing.