iWorld Professionals
iWorld Professionals is seeking a Machine Learning Analytics Engineer to play a key role with our client in deploying, maintaining, and optimizing production-level machine learning (ML) models . This position is a
remote
position
Machine Learning Analytics Engineer Position Summary:
This position bridges the gap between cutting-edge data science initiatives and real-world business outcomes-turning predictive insights into meaningful analytics and visualizations.
You'll work hands-on integrating ML models into scalable environments, ensuring their accuracy and performance, while creating dynamic Power BI dashboards that tell the story behind the data. This is an excellent opportunity for an engineer passionate about operationalizing machine learning and collaborating across technical and business teams.
Machine Learning Analytics Engineer Responsibilities:
Model Deployment & Integration:
Implement, test, and validate ML models in a cloud-based data platform (such as Snowflake) in collaboration with data engineering teams.
Model Lifecycle Management:
Monitor and maintain production ML models, proactively identifying issues related to accuracy, drift, and performance.
Continuous Improvement:
Retrain and optimize models based on new data inputs, changing business conditions, and feedback loops.
Automation & Monitoring:
Develop automated processes for model deployment, tracking, and retraining using Python and related ML libraries.
Data Visualization:
Design, develop, and maintain interactive Power BI dashboards to deliver actionable insights and highlight key performance metrics. Machine Learning Analytics Engineer Qualifications:
4-7 years of experience in machine learning engineering, applied data science, or analytics integration roles.
Proven experience deploying and maintaining ML models in production environments.
Strong proficiency in Python for automation, integration, and performance monitoring.
Hands-on experience with Snowflake or comparable cloud-based data platforms.
Advanced Power BI skills, including DAX, data modeling, and storytelling through visualization.
Familiarity withML model lifecycle management, from experimentation to production and retraining. Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field. Demonstrated ability to work well in a remote environment. Direct hire position with salary in the $130,000 - $145,000 range. Apply today to
iWorld Professionals
for immediate confidential consideration.
remote
position
Machine Learning Analytics Engineer Position Summary:
This position bridges the gap between cutting-edge data science initiatives and real-world business outcomes-turning predictive insights into meaningful analytics and visualizations.
You'll work hands-on integrating ML models into scalable environments, ensuring their accuracy and performance, while creating dynamic Power BI dashboards that tell the story behind the data. This is an excellent opportunity for an engineer passionate about operationalizing machine learning and collaborating across technical and business teams.
Machine Learning Analytics Engineer Responsibilities:
Model Deployment & Integration:
Implement, test, and validate ML models in a cloud-based data platform (such as Snowflake) in collaboration with data engineering teams.
Model Lifecycle Management:
Monitor and maintain production ML models, proactively identifying issues related to accuracy, drift, and performance.
Continuous Improvement:
Retrain and optimize models based on new data inputs, changing business conditions, and feedback loops.
Automation & Monitoring:
Develop automated processes for model deployment, tracking, and retraining using Python and related ML libraries.
Data Visualization:
Design, develop, and maintain interactive Power BI dashboards to deliver actionable insights and highlight key performance metrics. Machine Learning Analytics Engineer Qualifications:
4-7 years of experience in machine learning engineering, applied data science, or analytics integration roles.
Proven experience deploying and maintaining ML models in production environments.
Strong proficiency in Python for automation, integration, and performance monitoring.
Hands-on experience with Snowflake or comparable cloud-based data platforms.
Advanced Power BI skills, including DAX, data modeling, and storytelling through visualization.
Familiarity withML model lifecycle management, from experimentation to production and retraining. Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field. Demonstrated ability to work well in a remote environment. Direct hire position with salary in the $130,000 - $145,000 range. Apply today to
iWorld Professionals
for immediate confidential consideration.