H2O.ai is the open source leader in AI with a mission to democratize AI for everyone. H2O.ai is transforming the use of AI with software with its category-creating visionary open source machine learning platform, H2O. More than 18,000 companies use open-source H2O in mission-critical use cases for Finance, Insurance, Healthcare, Retail, Telco, Sales and Marketing. H2O Driverless AI uses "AI to do AI" in order to provide an easier, faster and cost-effective means of implementing data science. H2O.ai partners with leading technology companies such as NVIDIA, IBM, AWS, Intel, Microsoft Azure and Google Cloud Platform and is proud of its growing customer base which includes Capital One, Progressive Insurance, Comcast, Walgreens and MarketAxes. For more information and to learn more about how H2O.ai is driving an AI Transformation, visit www.h2o.ai.
Responsibilities and Duties:
As a Data Scientist in H2O.ai Professional Services team you will work closely with Data Science teams on the Customer side and Customer Success, Enterprise Support, Product Engineering and Sales teams on the H2O side.
Your primary responsibilities would be to
- Deliver data science and/or machine learning professional services to the customer.
- The services include implementing or helping the customer implement a machine learning model to a customer facing business problems using H2O.ai suite of machine learning products.
- Provide/gather customer feedback so that you can work with the H2O.ai Engineering team to further enhance our products.
You additional responsibilities include
- Be the trusted solutions advisor for our customers and partners.
- Communicate effectively with a diverse audience of internal and external stakeholders consisting of: Engineers, business people, partners, executives.
- 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.
- Demonstrate machine learning solutions with engaging storytelling and technical accuracy.
- Architect, design, and deliver Machine Learning and Data Science solutions.
- 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.
Qualifications and Skills:
Education and Experience
- 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.
- Proficient in Python or R for data science. Java, Bash scripting, Scala Go are a plus
- Experience of distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc.
- Experience in Spark and/or Hadoop ecosystem
- Understanding of writing/interacting with web APIs, preferably REST/JSON or XML/SOAP
- Understanding of various databases - Relational, NoSql, document, columnar
System Engineering Skills
- 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)
- General understanding of concepts SSH, TLS, network connectivity, firewalls, authentication and authorization etc that are required in any enterprise grade service architecture/solution
- Experience of working in a customer facing environment, providing data science services
- Excellent communication skills (verbal and written, English language). Additional languages a plus.
- Amicable attitude. Aptitude to independently investigate and find solutions to problems; urge to learn/master new technologies. Maker mindset.
- Flexible work hours and time off.
- Opportunity to work closely with some of the best engineering talent and the best data scientists/Kaggle Grandmasters in the world.
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.
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