We have a great client based role for a data scientist / solutions architect for an innovative AI organisation.

Our client has is a machine learning platform designed for big data with APIs are available in R, Python, Scala, Java and REST and JSON,. The AI organisation employs the techniques of expert data scientists in an easy to use application that helps scale client's data science efforts. They work with a variety of clients in different industries, so they need great communication skills as well as data science.

Job Summary:

• 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 skilled at predictive modeling?
• Do you view communication skills just as important as technical ones? Can you listen to the needs of your peers and customers and adapt where need be? Can you write a technical proposal and explain it in simple terms?
• Do you 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 machine learning interpretability, automatic machine learning, model management, deployment pipelines, and GPU computing.

Responsibilities and Duties:

As a solutions architect / customer data scientist, you will work closely with sales directors to:

• Own account-related technical items and relationships
• Translate business use cases and requirement into technical ones
• Problem solve and assess technical problems, determine solutions, and work with internal engineering and customer teams to resolve them
• Demonstrate ML solutions with engaging storytelling and technical accuracy
• 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.
• Architect machine learning workflows and systems from data ingestion to model deployment
• 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
• Travel up to 50% (primarily domestic, occasionally international)

Qualifications and Skills

• Bachelor's degree in engineering, computer science, mathematics or related field. Graduate degree is a plus.
• Proven experience with performing customer facing activities as part of a pre-sales team or professional services team
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• visualization skills using R, Python or other languages and frameworks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Proven experience using statistical computer languages (R, Python, etc.) to manipulate data and draw insights from large data sets.
• Proven experience with data in Hadoop and /or Spark ecosystem
• Desirable: Maker mindset, coachable, and have an urge to learn/master new technologies

Our client 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.