About This Opportunity
As a customer data scientist you will help customers be successful in their AI Journey. You will aid them in leveraging AI in the organization for different use-cases, building successful models and deploying them in production environments, bringing GenAI capabilities in the AI journey of the customers, and ensuring that they get business impact and value.What You Will Do
- Deliver data science and/or machine learning professional services to our customers.
- Support customers by helping build custom data models, transformation, scorers/optimization loss functions/metrics that can be leveraged with H2O Driverless AI and help improve training performance for the customer use cases/domains.
- Demonstrate different use cases and data science capabilities by building end to end AI Applications using H2O products and solutions.
- Design and run training sessions for our customers in data science concepts as well as using H2O products. Training will need to be able to be delivered to audiences with varying data science skills and abilities.
- Help customers understand the nuances of data science, expert settings of H2O Driverless AI and H2O open source, and the strategies of experiment tuning that you would use to incrementally improve model performance. This also includes explaining model performance, model interpretability, and post deployment model monitoring concepts so as to ensure the business is making the right decisions on the model predictions.
- 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.
- Participate in the development of ML solutions and AI applications for internal use, contributing to the advancement of our technology stack.
- Build and deploy machine learning models and AI applications to address customer-specific challenges.
- Work closely with cross-functional teams to gather, preprocess, and analyze data to develop data-driven solutions.
What You Bring
- Proven experience in data science, machine learning, and AI with a minimum of 2 years of hands-on experience.
- Experience in customer facing while dealing with different teams – technical, business, domain people.
- Experience in delivering technical sessions with different customer teams
- Interest in Generative AI and Large Language Models (Prompt Engineering, Retrieval Augmented Generation, LLMOps, Making custom LLM models, fine tuning etc, Guardrails)
- Proficiency in programming languages such as Python.
- Experience with solving machine learning problems using H2O ML products (plus), Python, R
- Knowledge and experience using a variety of machine learning techniques (supervised/unsupervised, clustering, decision tree learning, neural networks, etc.) and their real-world advantages/drawbacks/tuning techniques.
- Experience 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.
- In depth understanding of machine learning algorithms and experience applying Gen AI/ML to solve real work problems, including deployment of end to end ML pipelines
- Strong problem-solving skills and the ability to work independently and as part of a team.
- Excellent communication and presentation skills, with the ability to convey complex technical concepts to non-technical stakeholders.
