Overview
Skills
Job Details
Title - ML Integration and Analytics Engineer
Location-Rochester, NY-Onsite Role
Duration Full Time
Job Summary:
Machine Learning Integration and Analytics Engineer would be Responsible for deploying, maintaining, and enhancing machine learning models within the Snowflake environment,
while also developing and refining Power BI dashboards. This role serves as the bridge between advanced machine learning outputs and actionable business insights, ensuring models and dashboards adapt to evolving requirements.
Essential Functions:
ML Code Integration: Deploy, test, and validate ML models in Snowflake in collaboration with data engineering teams.
Model Maintenance: Monitor and support existing models, addressing accuracy, performance, and operational issues.
Model Adaptation: Recalibrate and enhance models based on new business inputs, data sources, and evolving use cases.
Visualization Development: Design, develop, and maintain Power BI dashboards that adhere to modern visualization and storytelling best practices.
Visualization Maintenance: Update and enhance dashboards with new KPIs, metrics, and analytical requirements.
Collaboration: Work closely with data scientists, engineers, and business stakeholders to translate technical outputs into accessible insights.
Management Responsibility:
- Machine Learning Integration and Analytics Engineer is an individual contributor and operates under the general direction of the Enterprise Architecture
Education and Experience:
- Bachelor's or master's degree in a quantitative field such as statistics, math, comp. science, data science
- Experience: 4 7 years experience in data science, predictive analytics, or related roles preferably in retail industry
- Proven experience deploying ML models into production environments.
- Proficiency in Python for ML model integration, automation, and performance monitoring.
- Familiarity with Snowflake and its integration with ML workflows.
- Strong Power BI development skills, including DAX, data modeling, and visualization best practices.
- Understanding of ML model lifecycle management (evaluation, retraining, adaptation).
Knowledge & Skills:
- Strong analytic and critical thinking skills; Strong data analysis & analytical problem-solving skills
- Excellent verbal and written communication skills with the ability to present data and complex terminology in an easily understood and concise way
- Ability to interact with business users, ask the right level of questions, and transform business needs into technology enabled solutions
- Ability to suggest, drive and govern technological best/proven practices
- Ability to operate comfortably and effectively in a fast paced, highly cross functional, rapidly changing environment.
- Must be able to manage multiple tasks and changing priorities
- Strong team collaboration across Business / IT / 3rd Party Partners
- Share and work in accordance with our values
Work Environment & Physical Requirements:
This job operates in a professional office environment. This role routinely uses standard office equipment such as computers, phones, photocopiers, scanners and fax machines.
Position requires prolonged periods of sitting/standing at a desk and working on a computer.
Ability to work standard business hours with the flexibility to work evenings, weekends and holidays as needed. Occasional travel required.
Regards,
Sai Srikar
Email: