Staff Data Scientist - Growth & Marketing ($400k - $500k)

Baton Corporation Ltd•New York, NY

14h•$400,000 - $500,000•Onsite

About The Position

Baton Corporation is seeking an experienced and versatile Data Scientist to join their team. This role offers the opportunity to identify opportunities, design and implement solutions, and measure their impact across the product in a fast-paced environment. The Data Scientist will collaborate with cross-functional teams and own projects from conception to completion. Key responsibilities include owning the measurement and analytics framework for marketing and paid acquisition efforts, developing frameworks for understanding key marketing metrics, designing and analyzing experiments, building models and analytical tooling, partnering with Growth and Marketing teams, combining various data sources for a complete view of the acquisition funnel, building foundational data models and dashboards, and identifying opportunities to improve marketing data infrastructure. The role also involves contributing to the wider Data Science function.

Requirements

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, with the ability to work independently across large and complex datasets.
Deeply familiar with the challenges of measuring paid marketing performance, including 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 used to measure marketing effectiveness.
Comfortable working with metrics such as CAC, LTV, ROAS, retention, conversion and payback, and understand how those metrics interact across the customer lifecycle.
Able to move beyond reporting what happened and determine why it happened, what will happen next and what we should do about it.
Comfortable building data models and lightweight pipelines, ideally with tools such as dbt, Dagster and BigQuery.
Experienced with data visualisation and dashboarding tools and capable of creating clear, decision-oriented reporting for non-technical stakeholders.
High-agency and comfortable owning ambiguous, high-impact problems from initial question through to recommendation and implementation.
An excellent communicator who can work closely with Marketing, Product and Engineering teams and influence decisions through data.
Strong product and commercial intuition, with an interest in understanding not just marketing performance but the broader behaviour of our users and market.

Nice To Haves

Experience with crypto, blockchain or on-chain data is beneficial but not essential.
Experience working with large-scale paid acquisition budgets across channels such as Meta, Google, TikTok, X or other major advertising platforms.
Experience developing or implementing marketing mix modelling, multi-touch attribution, incrementality testing or other advanced marketing measurement frameworks.
Experience building LTV, propensity, conversion or user-quality models used to inform acquisition strategy or bidding decisions.
Experience working with advertising platform APIs, mobile attribution platforms or customer data platforms.
Experience operating within a high-growth consumer product, marketplace, fintech, gaming or social platform.
Experience with machine learning methods applied to growth, marketing or user behaviour.
Experience with crypto, blockchain or on-chain data, or a demonstrated interest in the space.
Familiarity with data visualisation and modelling tools such as Omni.

Responsibilities

Own the measurement and analytics framework for our growing marketing & paid acquisition efforts, helping determine where and how we should deploy significant marketing budgets.
Develop frameworks for understanding incrementality, attribution, CAC, LTV, ROAS, payback periods and channel efficiency, ensuring we optimise for genuine business impact rather than platform-reported performance.
Design and analyse experiments across creative, audience, channel, bidding and landing-page strategies to identify what drives incremental user acquisition, engagement and revenue.
Build models and analytical tooling to understand user quality and predict downstream value across different campaigns, channels, cohorts and acquisition sources.
Partner closely with Growth and Marketing to turn complex data into clear recommendations on budget allocation, campaign strategy and where to scale or reduce spend.
Combine advertising platform data with first-party product, behavioural and on-chain data to build a complete view of the acquisition funnel and customer lifecycle.
Build foundational data models, dashboards and automated reporting that allow teams to understand marketing performance in real time.
Identify opportunities to improve our marketing data infrastructure, tracking and eventing, working closely with Engineering to ensure we have reliable data from impression through to downstream product behaviour.
Contribute to the wider Data Science function across product performance, experimentation, user behaviour, ecosystem analysis and competitive intelligence.