Who We Are

At Domino Data Lab, we have an ambitious vision for data science. Our customers are the most sophisticated analytical organizations in the world, including companies like Bristol Myers Squibb, Allstate, Bayer, and Red Hat and more. Our platform helps data science teams accelerate research, increase collaboration, and rapidly deploy predictive models. Backed by Sequoia Capital, Coatue Management, Bloomberg Beta, and Zetta Venture Partners, we are at the epicenter of the data science revolution, helping companies develop the next breakthrough in medicine, build better cars, and modernize customer experiences.

What We Are Building

Domino is assembling a world-class Field Data Scientist team dedicated to furthering our mission to unleash the power of data science. Our Field Data Science team sits at the core of the customer success organization. You would be joining a growing team that is part of a strategic initiative to expand our services and shape the organization's direction. Domino is dedicated to the long term success of team members and invests heavily in continuous education.

What Your Impact Will Be

Our customers love their Domino Field Data Scientists. As a senior member of our team, you will partner with customers to create solutions and strategies to address critical business problems.  You will educate customers on new topics in data science and MLOps. You will help customers see the impact of Domino on their bottom line which will accelerate the adoption. At the same time, you will work closely with many parts of Domino such as Product, Solution Architecture, Field Engineering, and Application Engineering, playing a key role in the overall sucess of the company. 

Responsibilities

• Work with customers to design and implement solutions across the entire data science lifecycle
• Analyze current open source technologies used within the customer and help them optimize their technology stack while taking advantage of what you will learn about Domino platform features
• Build deep relationships with senior technical members within customers to enable them to be Domino experts and advocates 
• Think strategically about customer business and technical challenges while working closely with Domino Customer Success Managers to bring about real impact for the customer
• Translate customer needs into actionable items for Domino’s product and engineering teams
• Contribute to the Domino’s Field Solution Engineering Council to build reusable project accelerators or assist existing field teams with solutioning work in the broader ML and analytics ecosystem
• Engage with external communities, by presenting at industry conferences, speaking at external meetups, and contributing to the Domino Data Science Blog
• Stay hungry and always be learning
• Some travel will be required (up to 25%) but there is flexibility with your circumstances

Qualifications

We are looking for an experienced and motivated data science technologist who possess a unique balance of technical depth, understanding of the ML ecosystem, the ability to connect technology with measurable business value, and strong interpersonal skills. The ideal candidate will be self-motivated with a proven track record of building innovative solutions in the analytics and data science space.

• Previous customer-facing consulting experience and 8+ years of solution engineering or data science/ML engineering experience 
• A degree in computer science, statistics, applied math, physics, or other quantitative subject area (Masters or PhD preferred)
• Will accept a suitable combination of education and experience
• Experience with frameworks such as TensorFlow or PyTorch
• An expert in modern theory, development, and implementation of computer vision or natural language understanding with deep nets
• Proven ability to work with large datasets utilizing distributed computing frameworks such as Spark, Ray, Dask, or MPI
• Strong general Python development skills as well as significant experience with Python data science packages and frameworks (similar R experience is highly desirable) 
• The ability to troubleshot Python environments, manage package dependencies, and work with Linux systems
• Comfort and experience with Git and CI/CD workflows
• An understanding of Docker and Kubernetes (experience containerizing data science models and pipelines is a plus) 
• Experience in productionalizing ML pipelines is highly desirable
• Working experience in one of the main cloud providers like AWS, GCP, Azure is highly desirable
• Experience as a technical leader mentoring more junior staff, teaching technical concepts, and delivering workshops