About the company Qualified is the #1 conversational sales and marketing platform for Salesforce, on a mission to disrupt how B2B companies meet with their buyers.
Headquartered in San Francisco, Qualified was founded in 2018 by serial entrepreneurs Kraig Swensrud (former CMO of Salesforce.com) and Sean Whiteley, a duo with a proven track record in enterprise software. Their first company, search marketing firm Kieden, was acquired by Salesforce in 2006, Their second company, online survey and customer experience platform GetFeedback, was acquired by Campaign Monitor in 2014, and later acquired by SurveyMonkey in 2019. Qualified is an early-stage, fast-paced, fast-growing startup in the SOMA area of San Francisco. The company has raised $68M in venture funding, and is backed by Norwest Venture Partners, Redpoint Ventures, and Salesforce Ventures.
Qualified has three main values that are carried throughout everything they do:
Customers First, Always: Prioritize the customer above everything else. Build a product that our customers love. Establish ourselves as their trusted advisor and do “whatever it takes” to make them successful. Only when our customers win do we win.
One Team: We’re all in this together with a shared goal: grow the business. Work as a team, win as a team. Collaborate, strategize, and brainstorm across departments to deliver A+ work.
Think Big, Move Fast: We’re defining a new category. Fast-paced innovation is the name of the game. We look forward. We reimagine. We throw out new ideas. We test things. We move quickly. We challenge the norm. We don’t settle for the status quo.
On the heels of their Series B financing, Qualified is looking to grow the team so that they can do even more, even faster; they’re focused on delivering our customers more innovation, additional services, an expanded product portfolio, and even deeper ties into the Salesforce CRM platform. Qualified is looking for folks that are fired up about joining a fast-paced, fast-growing company that is doing big things.
Job description
We would like to bring on board our first Senior Applied Machine Learning Scientist to join our fast-growing Engineering team to lead the work on our statistical data models/services. We are generating vast amounts of data from our main product and we want to deepen our usage of it. Establishing high-quality data assets, data infrastructure, and data science capabilities is critical for the company's continued success. We plan to invest heavily in data science and machine learning to drive strategic business decisions, power key product features, and solve problems that directly improve our customers’ experience.
This is a key leadership role within the team, with broad strategic and technical responsibilities, an opportunity to directly influence the direction of the business, and significant growth potential. You will spearhead the development of shared ML infrastructure that will allow the team to more effectively scale.
As a Senior Applied Machine Learning Scientist at Qualified, you will
Lead end-to-end process including conception, development, production, deployment, and monitoring of data and machine learning models and services
Be entrepreneurial and collaborate with key business partners to identify potential high-value applications of machine learning technology to our domain.
Work in conjunction with product and platform engineers to scale our data infrastructure in line with the needs of the company (i.e. data acquisition, ETL pipelines, reporting infrastructure, etc.)
Advance the state-of-the-art machine learning and NLP algorithms for real-world large-scale applications, in relation with current and future scope of product.
Work closely with the leadership team to define and deliver on the company strategic roadmap, primarily focusing on potential machine learning interventions.
Work with the engineering leadership to build and coach a world-class team of data scientists, data engineers and machine learning engineers
Who you are
At least four years of industry experience as a data scientist / ML engineer in high-growth environments
MS or PhD in Computer Science, Engineering, Economics, Statistics, or another quantitative discipline
Solid experience applying machine learning to real-world data problems and deploying scalable models into a production environment
Experience building robust ML infrastructure, applying engineering best practices.
Strong coding experience. Experience with open-source ML libraries and platforms.
Excellent communication skills and an ability to translate business context and intuition into data-oriented hypotheses to drive impact.
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