Company
Operation
DataScienceConsultant
“Data Science Consultant. Skills: SQL, Python, data modeling, EDA. partnering and working closely with our COO. working closely with our data team”
What You'll Achieve.
quick value generated; Answered business questions; Working data models; transformations; naming conventions; support those answers durably; lightweight running, living view of what's been built; lightweight running, living view of what's coming next
Industry & Context.
analytical instinct; ability to translate ambiguous business questions; judgment to know which questions are actually worth answering; perform EDA to answer the questions; Answered business questions
in-office in Mountain View
What They're Looking For.
Must Have
3+ years of experience as a data scientist, analytical instinct, ability to translate ambiguous business questions into well-defined metrics, judgment to know which questions are actually worth answering, Hands-on with SQL, Hands-on with Python, comfortable doing real EDA, Enough engineering chops to collaborate with our data eng team, make sound calls about data modeling, make sound calls about naming, make sound calls about transformation layer design, Comfortable asking questions, Comfortable making suggestions, Comfortable pushing back in executive meetings, practical bias
Nice to Have
AI-native builder, leveraging latest tools and AI-assisted coding, familiarity with the platforms and data sources we use (Stripe, HubSpot, PostHog, customer. io, Google Analytics)
What You'll Do.
partnering and working closely with our COO
working closely with our data team
doing real hands-on collaborative work
lightweight orientation on existing pipelines
lightweight orientation on warehouse
lightweight orientation on Metabase setup
Stakeholder conversations with leaders
Align on the first ~10 most important metrics
Align on the first ~10 most important questions
work through that first batch
define the metrics precisely
perform EDA to answer the questions
ship dashboards or analyses
build out the data models
build out naming conventions
build out pipeline pieces
move to another batch
Answered business questions
well-designed foundations
How You'll Work.
Team & Collaboration
partnering and working closely with our COO; working closely with our data team; doing real hands-on collaborative work; Stakeholder conversations with leaders across Product, Marketing and other teams; collaborate with our data eng team; pushing back in executive meetings
Communication Scope
Comfortable asking questions; Comfortable making suggestions; Comfortable pushing back in executive meetings
Process & Methodology
practical bias, close projects, answer questions iteratively
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