Who we are

At Domino Data Lab, we have an ambitious vision for data science. Our platform helps data science teams accelerate research, increase collaboration, and rapidly deploy predictive models. Our customers are the most sophisticated analytical organizations in the world, including companies like Bristol Myers Squibb, Allstate, Bayer, and Red Hat. 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, or recommend the best song play next.

What we are building

As the Director of Docs and Training, you will be responsible for leading the development and implementation of Domino Data Lab's documentation and training strategy. The ideal candidate will have experience creating technical documentation and training materials for enterprise software, as well as a strong understanding of machine learning and data science use cases and core IT administration and management needs.

We are looking for a hands-on leader who can coordinate and source great product documentation from subject matter experts in product management, product marketing, field data scientists, solution architects and more while creating a set of compelling collateral which clearly conveys the value of Domino DataLab to customers and prospects while also helping users maximize their impact for their business using Domino. With a focus on data-driven decision making, this role will be instrumental in ensuring that customers, partners, and internal teams have the resources they need to fully leverage the capabilities of the platform.

What we look for in this role

Documentation expertise at an enterprise B2B product (eg Databricks, DataRobot, Splunk)

• Driven significant overhaul of product documentation website and content with measurable impact
• Worked in a startup environment where you've been a solo tech writer or led a small docs team. You've written documentation about complex software for data scientists and IT administrators, worked on API docs, and used a "docs as code" mode of authoring.

Domain expertise

• ML Platform knowledge, experience. Familiarity with Databricks v Sagemaker v DataRobot is a goal; actual ML model training/deployment expertise is preferable
• Distributed/cloud computing expertise is important (eg Kubernetes, Docker)
• Expertise with digital transformation, business process automation, high performance computing, security or networking are nice to have
• Strong experience working with related competitor products such as Databricks, Sagemaker, DataRobot, Dataiku, or Azure Machine Learning is highly desirable.

Demonstrated excellence

• Excellent written and verbal communication skills, with the ability to create clear, accurate, and accessible documentation for a wide range of audiences.
• Strong project management skills, with the ability to lead cross-functional teams and deliver complex projects on time and within budget.
• Experience with data analysis and the ability to use data to measure the impact and adjust the documentation and training strategy accordingly.

Experience creating and delivering training programs, including in-person, webinars, and online tutorials.

What we value

• We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply
• We value a growth mindset. High-performing creative individuals who dig into problems and see the opportunities for success
• We believe in individuals who seek truth and speak the truth and can be their whole selves at work
• We value all of you that believe improving is always possible. At Domino, everything is a work in progress – we can do better at everything
• We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company

Compensation range

Based on pay transparency guidelines, a reasonable expectation for the salary range for this role is $174,000-260,000 USD Annually. Information on our competitive total rewards package, including our benefits can be found here. Individual salaries are determined by evaluating a variety of factors including geography, cost of labor, experience, skills, education, and internal equity.

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