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Data Scientist, Product

higgsfieldaiAlmaty, KazakhstanEngineering & Product
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Salary
Not listed
Job type
Full-time
Posted
7 Sept 2026
Status
Open · checked 7d ago

About this role

Data Scientist, Product is a full-time role based in Almaty, Kazakhstan, designed for professionals who want to transition the company from treating users identically to taking individualized, data-backed actions. This position suits growth, retention, or monetization data scientists who specialize in turning predictive models and causal measurement into real-world business outcomes.

Role Overview

Data Scientist, Product takes charge of the models that determine user targeting and the causal analytics required to measure financial impact. This position requires owning churn prediction, uplift modeling, lifetime value calculations, and experimentation to ensure every discount, credit voucher, and campaign changes user behavior rather than spending margin on users who would convert anyway.

Key Responsibilities

Build separate machine learning models for subscriber churn and downgrade prediction alongside repeat-purchase propensity for credit-pack buyers.
Own incrementality and uplift modeling for all targeted user interactions, including discounts, trials, upgrade prompts, and win-back campaigns.
Design and maintain permanent randomized holdouts to ensure uplift remains trainable and measurable.
Collaborate with Legal to navigate consumer-protection and consent regulations regarding personalized pricing and discounting.
Manage cohort-based lifetime value on contribution margin, accounting for refunds, chargebacks, credit expiry, and compute consumption.
Design and read pricing, packaging, and lifecycle experiments in partnership with the product analytics team.
Manage the end-to-end model lifecycle, including framing decisions, feature engineering, training, batch scoring, monitoring for drift, and computing financial return.

Requirements

Experience shipping models that directly modified business actions toward real users, moving beyond offline benchmarks and notebooks.
Depth in a minimum of two areas: churn and propensity modeling, uplift and causal machine learning, subscription economics and lifetime value, or large-scale experimentation.
Proven causal literacy covering randomized holdouts, incrementality, Qini curves, uplift curves, and selection effects.
Strong programming skills in Python and SQL to handle cohorts, funnels, retention on raw data, gradient boosting, and reliable scheduled scoring pipelines.
Clear written and spoken English proficiency at a B2+ level or higher.

Skills and Tools

Python
SQL
Gradient Boosting

About the Company

Higgsfield ai operates in Almaty, Kazakhstan, building at the frontier of AI-powered video creation and creative tools with millions of users worldwide and billions in revenue run rate.

How to Apply

Candidates should apply on the official company careers page.

Skills and tech stack

Questions candidates ask

Where is this job located?

This position is located in Almaty, Kazakhstan.

What level of English is required?

Applicants must have clear written and spoken English at a B2+ level or higher.

Does this role involve training generative video models?

No, training or fine-tuning generative video models belongs to the R&D ML Engineer roles, not this position.

What does the hiring process look like?

The hiring process consists of a 30-minute screening call, a 1-hour technical interview and case study, a 7-day practical home task, a 60-minute team interview, and a 1-month paid on-site trial.

Ready to apply?

The application is on the official higgsfieldai careers page.

Apply on company site