~27d ago

Staff Data Scientist, Growth and Marketing

United States·New Yorklead

OtherStaff Data Scientist

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Quick Summary

Key Responsibilities

attribution, incrementality, selection bias and platform reported metrics. Experienced designing and analysing experiments, including geo tests, holdouts,

Technical Tools

OtherStaff Data Scientist

Responsibilities

~1 min read

→An experienced Data Scientist with significant exposure to paid acquisition, performance marketing or growth analytics within a scaled consumer technology business.
→Highly proficient in Python or R and SQL, working independently across large and complex datasets.
→Deeply familiar with measuring paid marketing performance: attribution, incrementality, selection bias and platform reported metrics.
→Experienced designing and analysing experiments, including geo tests, holdouts, A/B tests or other causal inference approaches for marketing effectiveness.
→Fluent in CAC, LTV, ROAS, retention, conversion and payback, and how those metrics interact across the customer lifecycle.
→Able to move beyond what happened to why it happened, what will happen next and what should be done about it.
→Comfortable building data models and lightweight pipelines, ideally with dbt, Dagster and BigQuery, and experienced with visualisation and dashboarding tools for decision oriented reporting.
→A high agency owner of ambiguous, high impact problems from initial question through to recommendation and implementation.
→An excellent communicator who influences Marketing, Product and Engineering decisions through data, with strong product and commercial intuition.
→Experience with crypto, blockchain or on chain data is beneficial but not essential.

Requirements

~1 min read

Large scale paid acquisition budgets across Meta, Google, TikTok, X or other major platforms.
Marketing mix modelling, multi touch attribution, incrementality testing or other advanced measurement frameworks.
LTV, propensity, conversion or user quality models used to inform acquisition strategy or bidding.
Advertising platform APIs, mobile attribution platforms or customer data platforms.
High growth consumer product, marketplace, fintech, gaming or social platform experience.
Machine learning applied to growth, marketing or user behaviour.
Crypto or on chain data experience or interest.