Data Scientist & Developer Advocate — Platform Evangelist

MACHINE LEARNING TECHNOLOGIES LLC; St. Louis (MO); On-site; USD 83,000 - 152,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC is seeking a Data scientist/data modeler/AI to amplify a growing data platform. The role emphasizes evangelism, community building, and collaboration with data scientists across initiatives, including hackathons and workshops.

You will read code, help shape platform roadmaps, and promote best practices for data science tooling across AWS SageMaker, GCP, and Azure deployments, with a focus on scalable ML deployment and community growth.

Qualifications

• Perfect communication.
• Foster a developer community around Global Data Assets & Analytics platforms and technologies.
• Participate in and organize hackathons, workshops, and meetups to facilitate interaction and knowledge sharing, aligned with platform’s roadmaps.
• Build relationships with key influencers, community leaders, and other organizations to extend the platform’s reach and amplify its messages.
• Advocate for 600+ individuals in the data realm.
• Need to read code but will not be developing code.
• Evangelism and Promotion.
• Masters degree
• Data scientist, data modeler, artificial intelligence (AI)

Responsibilities

• Partner with members of the Data Science community to implement best practices and align with platform vision.
• Develop and contribute tools that simplify platform operations.
• Create educational content and provide technical support.
• Gather developer feedback and advocate for community needs; Foster a thriving data science community

Skills

Communication

Community building

Hackathons

Public speaking

Evangelism

Education

Master's degree in a relevant field

Tools

Python

R

Pandas

NumPy

scikit-learn

AWS SageMaker

GCP

Azure

MLOps

Job description

MACHINE LEARNING TECHNOLOGIES LLC is seeking a Data scientist/data modeler/AI to amplify a growing data platform. The role emphasizes evangelism, community building, and collaboration with data scientists across initiatives, including hackathons and workshops.

You will read code, help shape platform roadmaps, and promote best practices for data science tooling across AWS SageMaker, GCP, and Azure deployments, with a focus on scalable ML deployment and community growth.