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Senior Data Scientist
2 months ago
Data Science @ Pave
Data is truly at the heart of what we do here at Pave. So, it's no surprise that Pave Data Scientists are integral collaborators and strategic owners with company-wide impact. Our team members build data infrastructure, create and deploy ML models, define and evaluate metrics, and help create the tools our customers use to understand our unique data set.
How you'll contribute:
We're looking for a Senior Data Scientist to join our Market Data Team. The Market Data Teams prototypes and builds brand new data products, as well as leveraging data to improve our existing ones. You'll partner with Product Managers and go-to-market leaders to understand user needs, partner with Design to create early prototypes and explorations, then work with our Software Engineering team to scale your insights into high quality, compelling user-facing products.
The ideal fit for this role is someone who enjoys creating and innovating with data, is passionate about metrics and methods, and who is able to balance the need for technical complexity with user-facing simplicity. This person has a deep technical toolkit, but also knows that the highest value data products are not always the most complex.
Required skills and experience:
Have a Bachelors or other advanced degree in a quantitative discipline: statistics, operations research, social science, computer science, engineering, mathematics, economics, etc.
4+ years of experience in a Data Science role, preferably at a technology company.
Expert data manipulation skills with a proficiency in SQL.
Expert in statistical modeling with Python or R (e.g., clustering, regression, time series, Bayesian statistics).
Strong data intuition and creativity: you are able to design creative, useful, and accurate metrics, and have strong intuitions about where metrics go wrong.
Strong analytical problem solving skills: you have the ability to translate qualitative business questions into quantitative solutions.
Product- and business-minded: you enjoy using data to solve user pain points and business problems.
Strong ability to communicate technical outcomes to cross-functional audiences.
Ability to navigate (and bring structure to) ambiguity, with the ability to bring a project from 0 to 1.
Nice to haves:
Experience evaluating the performance of ML models (not that this is not an ML-specific role, but you will work closely with ML Engineers).
Experience with data transformations using dbt.
Experience building customer-facing data products.
Experience working with product managers, engineers, and/or designers.
A final note - we highly encourage you to apply for this role, even if you don't feel entirely qualified, or entirely sure. You never know
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