Data Scientist (Machine Learning)

TL;DR

Data Scientist (Machine Learning): Building and deploying production-grade machine learning models to directly impact marketing and business performance with an accent on improving LTV prediction, optimizing ML-driven costs, and driving key metrics. Focus on developing end-to-end ML pipelines, standardizing ML approaches, and providing technical input to ML infrastructure.

Location: Remote (Global) or in office

Company

hirify.global is an international company focused on building production-grade machine learning models to improve marketing and business performance for mobile subscription-based products.

What you will do

• Design, develop, and deploy machine learning models to production.
• Build and evolve end-to-end ML pipelines (data → features → model → inference → monitoring).
• Drive measurable impact on key product and commercial metrics such as LTV, ROAS, retention, and CAC.
• Standardize ML approaches within the team and provide technical input to analytics and ML infrastructure.
• Act as a domain expert and collaborate closely with Marketing, Product, and Data Engineering teams.

Requirements

• 3+ years of experience as a Data Scientist / ML Engineer.
• Experience working with mobile subscription-based products.
• Strong Python skills (production-level code) and strong SQL skills.
• Solid knowledge of classical machine learning algorithms, feature engineering, model evaluation, and bias–variance trade-offs.
• Hands-on experience with marketing models such as LTV, churn, cohort, funnel, attribution, incrementality, and uplift modeling.
• Experience with production ML systems and A/B testing.
• English level: Intermediate+.

Nice to have

• Experience with BigQuery.
• MLOps experience (Docker, CI/CD, model registries).
• Knowledge of causal inference, AutoML, and Bayesian models.
• Experience working with performance marketing data (Meta, Google Ads, Adjust).

Culture & Benefits

• Highly competitive compensation package with Performance Review practice.
• Flexible schedule and opportunity to work remotely or in a stylish and comfortable office.
• Respect for work-life balance (holidays, sick days).
• Additional medical insurance.
• Compensation for specialized training and conference attendance.
• Bright corporate events, gifts, restaurant lunches at company's expense (for in-office), and endless supplies of delicious food.