Magnify Technologies
Principal Data Scientist
Magnify Technologies, Seattle, Washington, us, 98127
The role
In this role, you will be responsible for:
Working with a variety of data sources provided by Magnify's customers and leveraging these to build models that predict future revenue expansion and churn; identify drivers for key events in the customer lifecycle (renewal, expansion, cancellation, etc.); and enable accelerating product adoption and usage.
Collecting and understanding customer needs, Magnify's vision, and stakeholder input to improve model accuracy and relevancy, and to develop new models and functionality to expand Magnify's products.
Innovating and providing thought-leadership to the Magnify team around future data science and machine learning opportunities, including expanded use of generative AI.
Partnering with the engineering team to build infrastructure that provides reliability, observability, and scalability to data science pipelines and model/product integrations.
Qualifications and Experience
Successful candidates are likely to have the following qualifications and experiences; we strongly encourage you to apply even if you don’t meet all of the items below.
Masters in Computer Science or related field; PhD preferred.
7+ years of experience working as a data scientist in a high growth, startup environment.
Strong knowledge and hands-on experience across machine learning, causal inference, experimentation, product analytics, revenue analysis, statistics, and/or optimization.
Ability and comfort operating with ambiguity in an early stage startup environment in which you may need to "bootstrap" data science infrastructure to complete projects.
Strong communication skills, both written and verbal, and the ability to successfully engage across audiences of varying backgrounds and technical proficiencies.
Passionate about delivering for users and collaborating with teammates.
Have a strong bias for action, a track record of moving quickly, and the ability to identify where and when scrappiness is the right approach versus those places where deeper rigor is required.
Seattle-area preferred; This role is remote eligible within the United States.
No third parties / recruiters please.
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In this role, you will be responsible for:
Working with a variety of data sources provided by Magnify's customers and leveraging these to build models that predict future revenue expansion and churn; identify drivers for key events in the customer lifecycle (renewal, expansion, cancellation, etc.); and enable accelerating product adoption and usage.
Collecting and understanding customer needs, Magnify's vision, and stakeholder input to improve model accuracy and relevancy, and to develop new models and functionality to expand Magnify's products.
Innovating and providing thought-leadership to the Magnify team around future data science and machine learning opportunities, including expanded use of generative AI.
Partnering with the engineering team to build infrastructure that provides reliability, observability, and scalability to data science pipelines and model/product integrations.
Qualifications and Experience
Successful candidates are likely to have the following qualifications and experiences; we strongly encourage you to apply even if you don’t meet all of the items below.
Masters in Computer Science or related field; PhD preferred.
7+ years of experience working as a data scientist in a high growth, startup environment.
Strong knowledge and hands-on experience across machine learning, causal inference, experimentation, product analytics, revenue analysis, statistics, and/or optimization.
Ability and comfort operating with ambiguity in an early stage startup environment in which you may need to "bootstrap" data science infrastructure to complete projects.
Strong communication skills, both written and verbal, and the ability to successfully engage across audiences of varying backgrounds and technical proficiencies.
Passionate about delivering for users and collaborating with teammates.
Have a strong bias for action, a track record of moving quickly, and the ability to identify where and when scrappiness is the right approach versus those places where deeper rigor is required.
Seattle-area preferred; This role is remote eligible within the United States.
No third parties / recruiters please.
#J-18808-Ljbffr