H2O.ai is hiring a
Customer Data Scientist
H2O.ai is the leading AI cloud company, on a mission to democratize AI for everyone. Customers use the H2O AI Hybrid Cloud platform to rapidly solve complex business problems and accelerate the discovery of new ideas. H2O.ai is the trusted AI provider to more than 20,000 global organizations, including AT&T, Allergan, Bon Secours Mercy Health, Capital One, Commonwealth Bank of Australia, GlaxoSmithKline, Hitachi, Kaiser Permanente, Procter & Gamble, PayPal, PwC, Reckitt, Unilever and Walgreens, over half of the Fortune 500 and one million data scientists. Goldman Sachs, NVIDIA and Wells Fargo are not only customers and partners, but strategic investors in the company. H2O.ai’s customers have honored the company with a Net Promoter Score (NPS) of 78— the highest in the industry based on breadth of technology and deep employee expertise.
The world’s top 20 Kaggle Grandmasters (the community of best-in-the-world machine learning practitioners and data scientists) are employees of H2O.ai. A strong AI for Good ethos to make the world a better place and responsible AI drive the company’s purpose.
Please join our movement at www.H2O.ai
As a Customer Data Scientist, you will collaborate with Data Science teams on the customer side, work on diverse use cases from several industry verticals, and leverage domain expertise in data science and H2O platform to help customers achieve their AI objectives. This is an opportunity to work closely with some of the best engineering talent and the best data scientists/Kaggle Grandmasters in the world.
What You Will Do
Enable customers to solve complex data science problems by providing consultation and guidance on use case identification, feature engineering, model selection and tuning, model deployment and optimization. Architect, design, and deliver Machine Learning and Data Science solutions. Demonstrate ML solutions with engaging storytelling and technical accuracy. Help customers understand model performance, model interpretability, and post deployment model monitoring concepts, and enable them to maximize power of the H2O platform, via training, workshop, and ongoing consultations. Act as a subject matter expert in H2O platform and data science. Collaborate with Sales, R&D, and Product teams, to enhance H2O functionality Translate business cases and requirements into value based technical solutions through the architecture of machine learning workflows and systems from data ingestion to model deployment. Present at meetups and webinars in the Data Science community, and be an integral part of the Maker culture of creating the best products and solutions. What We Are Looking For
Bachelor’s or a higher education degree in Computer Science/Engineering, Mathematics/Statistics Minimum 3 to 5 years of hands on experience solving data science problems in real world environment
Data Science Skills
Experience with solving machine learning problems using H2O ML products (plus), Python, R Knowledge and experience of using a variety of machine learning techniques (supervised/unsupervised, clustering, decision tree learning, neural networks, etc.) and their real-world advantages/drawbacks/tuning techniques. Knowledge and experience of using advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) for practical applications. Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. Knowledge and experience of implementing end to end Data Engineering pipelines Experience of visualizing and presenting (EDA) to stakeholders using H2O Wave (plus), or other standard data visualization libraries in the Python and R stacks or using Tableau/PowerBi. Understanding and experience with post production model monitoring tools like H2O ML Ops (plus) MLFlow etc.
Programming Languages & System Engineering Skills
Proficient in Python or R for data science. Java, Bash scripting, Scala Go are a plus Understanding of system engineering concepts and working in a linux based environment (OS fundamentals etc). Ubuntu and CentoOS/RHEL mainly. High level understanding of the cloud ecosystem, working with containers (docker etc)
Experience of working in a customer facing environment, providing data science consultation services Excellent communication skills. Amicable attitude. Aptitude to independently investigate and find solutions to problems; urge to learn/master new technologies. Maker mindset.
How To Stand Out From the Crowd
Experience of distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc. Experience in Spark and/or Hadoop ecosystem
Market Leader in Total Rewards Remote-Friendly Culture Flexible working environment Be part of a world-class team
Career Growth H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis.