At H2O.ai we see a world where all software will incorporate AI, and we’re focused on bringing AI to business through software. H2O.ai is the maker behind H2O, the leading open source deep learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark. Some of H2O’s mission critical applications include predictive maintenance, operational intelligence, security, fraud, auditing, churn, credit scoring, user based insurance, predicting sepsis, ICU monitoring and more in over 10,000 organizations. H2O is brewing a grassroots culture of data transformation in its customer communities. Customers include Capital One, Progressive Insurance, Zurich North America, Transamerica, Comcast, Nielsen Catalina Solutions, Macy’s, Kaiser Permanente and many more
- Can you learn demonstrations (demos) built with R and/or Python? If you think of a cool demo and it doesn't exist, will you raise your hand to get it built?
- Can you sling code proficiently in at least one language used by data scientists and/or data engineers, and does it excite you to learn more?
- Are you a strong learner capable of coming up to speed quickly with new technologies?
- Do you view communication skills just as important as technical ones? Can you listen to the needs of your peers and customers? Can you write a technical proposal?
- Have a competitive drive to be the best you can be?
- Can you finish what you start? Can you own assignments given to you?
If the answer is "yes" to these questions, you potentially could be an excellent fit to join the team of customer engineering makers at H2O.ai. We deliver world-class solution experiences for our customers and drive revenue for our organization. Some of the technical projects you will work on include: training advanced machine learning models at scale in distributed environments, influencing next generation data science tools and data products, and pioneering ideas and products in new areas, such as GPU machine learning, machine learning interpretability, automatic machine learning, model management, & deployment pipelines.
As a solutions architect / customer data scientist, you will work closely with sales directors to:
- Be the technical expert and data scientist leader for sales cycles
- Own account-related technical items
- Translate business use cases and requirement into technical ones
- Problem solve and assess technical problems, determine solutions, and work with internal and customer teams to resolve them
- Architect machine learning workflows and systems
- Create, design, and deliver compelling presentations on complex & technical concepts
- Craft statement of work, responses for proposals/information, and all written communication required to engage customers.
- Demonstrate product solutions with engaging storytelling and technical accuracy
- Communicate effectively with internal and externally to a diverse audience, including: engineers, business people, and executives. Audiences will be large and small, and interactions will be in-person and online.
- Drive field feedback back into product development
- Be hands-on for all technical activities throughout the sales cycle
- Focused on customer experience and sales objectives
- Travel up to 50% (primarily domestic, occasionally international)
Education and Experience
- Bachelor's degree in engineering, computer science, mathematics or related field. Graduate degree is a plus.
- 2+ years’ experience with performing customer facing activities as part of a pre-sales team or professional services team
- 2+ years’ experience with machine learning and data mining
- 2+ years’ using R or Python for data analytics
- 2+ year working with data in Hadoop and /or Spark ecosystem
- Desirable: Maker mindset, strong learner and coachable
- Desirable: Fearless problem solver, strong technical abilities, accountable team player
Work location: Multiple locations across the United States
H2O.ai is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of race, gender, sexual orientation, gender identity, disability or veteran status.