Lead Data Scientist (AdTech)

Location: Remote from Lima, Peru; most of the company works East Coast hours.

Company

hirify.global is a discovery and conversion company connecting consumer brands in finance, travel, and entertainment with partner customer acquisition at scale. The company is profitable, bootstrapped, headquartered in South Florida, and operates with a remote-first team across 18 countries.

What you will do

• Build models that select the auto insurance carrier most likely to convert each shopper on the click wall.
• Own buying models for media spend and optimize them against ROAS.
• Use carrier conversion data, including quotes, policies, and acquisition cost, in production models.
• Frame business problems, find and prepare data, build and validate models, and manage deployment and monitoring end to end.
• Develop approaches for delayed outcomes, sparse sessions, repeat users, market drift, and bid-driven training data.
• Work with an ML engineer on production implementation and expand the scope from auto insurance to other verticals over time.

Requirements

• 5+ years of hands-on applied data science experience with measurable business impact.
• Experience building models that drove paid media decisions, including spend, bidding, or ad serving; attribution and reporting alone do not qualify.
• Ability to explain self-built models in detail, including loss functions, architecture choices, and neural network fundamentals.
• Experience handling the effect of current bids on future training data, including late labels, sparse features, or data drift.
• End-to-end ownership of models from finding data and building through deployment and monitoring, with an independent point of view.
• Expert Python and SQL.

Nice to have

• Experience spending real ad budgets in live auctions.
• Experience with large-scale ranking or recommendation systems.
• Ability to explain technical tradeoffs to non-technical partners in plain language.
• Experience designing for auction feedback loops, selection bias, and exploration.
• Hands-on neural network work, including embeddings of text, creative, or user behavior.
• AWS data science experience with ECS, S3, Athena, or SageMaker.
• CI/CD deployment experience.

Culture & Benefits

• Remote-first work environment.
• Focus on ownership, measurable impact, direct feedback, and adapting to change.
• Diverse and inclusive team culture.
• Equal Employment Opportunity workplace.