ML Solutions Architect

The Value You Will Add:

• Be a Kumo platform superuser - understand the product in and out and how it should be used to solve customer problems.
• Lead the technical discovery to understand the alignment between what Kumo offers and prospective customer expectations.
• Conduct product demos of Kumo solving ML problems in a variety of verticals, including finance/fraud, growth/marketing, personalization/commerce, and forecasting/optimization.
• Guide the customer to achieve meaningful wins on high-impact ML problems, by leveraging your problem-solving skills, data science knowledge, and industry experience.
• Be hands-on, to help customers overcome challenges they may encounter in achieving sufficient model performance, or integrating Kumo into their production systems.
• Lead architecture reviews and security assessments.
• Maintain meaningful relationships with technical influencers and champions within ML teams, both pre and post-sale.
• Educate current Kumo users on how to successfully use our product, best practices, etc. so that they increase usage across a larger and larger number of internal workloads.
• Provide market and customer feedback to the Product and Engineering team to refine feature specifications and the product roadmap.
• Create broader processes for each customer to go through to ensure we can drive repeatable successes in PoCs.
• Generate Kumo platform educational materials to disseminate amongst current users or prospects.

Your Foundation:

• Someone who finds genuine satisfaction in solving customer ML problems and helping them deliver value to the business.
• 5+ years of relevant professional experience working with external customers in deploying AI/ML/data science solutions in production for customers.
• Proficiency with ML and data science fundamentals, at the level of a bachelors/graduate program.
• Persuasive communication – ability to present, speak, demo well to customer stakeholders and convince them to partner with Kumo!
• Self-starter, motivative, resourceful and persistent: demonstrated ability to structure complex problems, take the initiative, and identify creative solutions to deliver outcomes in the face of obstacles.
• Knowledge of common data science tools around SQL-based data warehousing (eg. Snowflake, Databricks, DBT), BI tools (eg. Tableau, Looker), workflow orchestration, and ML Ops.
• Excellent spoken and written English skills.
• Fluency with scripting in Python.
• Ability to work effectively across time zones. Teammates will be located from PT to CET time zones. Customers will be in GMT/CET, while occasionally as far as SGT.