Staff Data Scientist, Marketing Science - Founding Role

batoncorporation

New York (NY)

On-site

USD 180,000 - 260,000

Full time

5 days ago
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Job summary

Baton Corporation, the creator of pump.fun, is hiring a Staff Data Scientist in Marketing Science in New York to own the mathematics behind paid growth and optimization across multiple channels. You will build models, design experiments and work closely with the paid acquisition team to direct a multi-million-dollar budget.

You will write models yourself, validate them with experiments, and deliver decision-ready insights.

Qualifications

  • Advanced training in mathematics, statistics or econometrics.
  • Hands-on experience building marketing mix or advertising response models.
  • Ability to derive insights from experiments and models and explain to non-specialists.

Responsibilities

  • Build marketing measurement system with Bayesian MMM, adstock, saturation, channel curves and uncertainty.
  • Design geo-experiments, conversion-lift tests, holdouts and synthetic controls to calibrate models.
  • Estimate marginal ROAS and CAC by channel and advise allocation decisions.
  • Develop LTV, retention and payback models linked to activation and trading activity.
  • Model new channels where data is sparse and justify approaches to leadership.
  • Set test roadmaps with the Head of Paid Acquisition & Performance Marketing.
  • Ship production-quality, versioned and testable code with data engineers.

Skills

Marketing mix modeling
Causal inference
Experiment design
Bayesian methods
Python or R production

Education

PhD, MSc or equivalent

Tools

PyMC
Stan
NumPyro
Meridian

Job description

Baton Corporation, the creator of pump.fun, is hiring a Staff Data Scientist in Marketing Science in New York to own the mathematics behind paid growth and optimization across multiple channels. You will build models, design experiments and work closely with the paid acquisition team to direct a multi-million-dollar budget.

You will write models yourself, validate them with experiments, and deliver decision-ready insights.

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