ML Ops Engineer

As an ML Ops Engineer at Quation, you will manage the deployment and integration of machine learning models into production. You’ll ensure end-to-end deployment of analytics solutions, manage large-scale data handling, and provide essential data visualizations. You will also collaborate with customer success teams to enhance usability, streamline analytical workflows, and simplify technical concepts for non-technical stakeholders. 

Years of Experience • 3 - 5 years of relevant experience in ML Ops, data deployment, and analytics project management. 

Budget • Compensation: Competitive and aligned with industry standards. 

Key Responsibilities

 • Lead and oversee timely completion of data analytics projects as part of the analytics implementation process.

 • Deploy analytics solutions, including applications and dashboards, accurately and within client timelines. 

• Assess business requirements and design analytical dashboards on cloud platforms for retail and digital brands.

 • Manage the full data science life cycle: data collection, preparation, modeling, evaluation, and scaled deployment. 

• Handle data at scale, deploying machine learning models with visualization capabilities in production.

 • Collaborate with customer success and category teams to identify and address client usability challenges.

• Communicate technical concepts in a simplified manner to business stakeholders.