Marketing Coordinator

Posted 12 Days Ago
Be an Early Applicant
Hiring Remotely in Skopje, Skopski
Remote
1-3 Years Experience
Artificial Intelligence • Cloud • Machine Learning • Software • Database
The Role
This role ensures that all marketing activities are expertly executed by creating and following low-lift processes across teams. Responsibilities include scheduling meetings, managing social media posts, coordinating product launches, updating the website, assigning design work, managing marketing database communications, and supporting events.
Summary Generated by Built In

Come and change the world of AI with the Kumo team!


Companies spend millions of dollars to store terabytes of data in data lakehouses, but only leverage a fraction of it for predictive tasks. This is because traditional machine learning is slow and time consuming, taking months to perform feature engineering, build training pipelines, and achieve acceptable performance.


At Kumo, we are building a machine learning platform for data lakehouses, enabling data scientists to train powerful Graph Neural Net models directly on their relational data, with only a few lines of declarative syntax known as Predictive Query Language. The Kumo platform enables users to build models a dozen times faster, and achieve better model accuracy than traditional approaches.


This role ensures that all marketing activities are expertly executed by creating and following low-lift processes across teams. 

Responsibilities

  • Schedule calls and manage calendar changes for key stakeholder meetings
  • Send action items, due dates, and reminders
  • Schedule all social media posts and partner with executives to ensure posts are made. Send reminders as needed
  • Coordinate product launch calendar and workback schedules for key decisions, stakeholders, and deliverables. Ensure stakeholders are reminded and are delivering in order to keep all projects on track.
  • Organize analyst, customer, and interviews with journalists as needed. Ensure all key decisions, stakeholders, and deliverables are identified, tracked, and on time.
  • Update the website, post blogs, add/remove events, and open tickets for website development work. Track and ensure website work is planned and delivered across internal stakeholders and web development team. 
  • Coordinate and assign all design work for the design team. Understand all incoming asks, timelines, and scopes to ensure designs are reviewed and finalized with each stakeholder.
  • Take responsibility for marketing database and marketing database communications in partnership with the Marketing Programs Manager to invite contacts to webinars, events, and inform them of news and announcements. 
  • Support events, run reports, order items, and other tasks as they are identified. 

Requirements:

  • College degree in Marketing, Communications, Business Administration, or similar. Or at least 1 year of similar experience.
  • Fluency in English.
  • Candidates should be available to work at least 4 hours a day overlapping the Pacific time zone.

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We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

The Company
HQ: Mountain View, CA
38 Employees
On-site Workplace
Year Founded: 2021

What We Do

Democratizing AI on the Modern Data Stack!

The team behind PyG (PyG.org) is working on a turn-key solution for AI over large scale data warehouses. We believe the future of ML is a seamless integration between modern cloud data warehouses and AI algorithms. Our ML infrastructure massively simplifies the training and deployment of ML models on complex data.

With over 40,000 monthly downloads and nearly 13,000 Github stars, PyG is the ultimate platform for training and development of Graph Neural Network (GNN) architectures. GNNs -- one of the hottest areas of machine learning now -- are a class of deep learning models that generalize Transformer and CNN architectures and enable us to apply the power of deep learning to complex data. GNNs are unique in a sense that they can be applied to data of different shapes and modalities.

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