Data Scientist

Location: Remote or office-based

Company

hirify.global develops scalable products and machine learning solutions used by millions, focused on measurable business impact.

What you will do

• Develop and improve an NGR forecasting system based on an ensemble of machine learning models.
• Build and deploy machine learning solutions for marketing and user behavior prediction using regression, binary classification, and multiclass classification.
• Design and optimize data marts and process large-scale datasets in ClickHouse.
• Build production machine learning pipelines and maintain Airflow DAGs for recurring model inference.
• Evaluate models with technical and business metrics, including WAPE, RMSE, ROAS, budget savings, and opportunity cost.
• Conduct exploratory data analysis, identify marketing growth opportunities, and translate model results into actionable business insights.

Requirements

• 2+ years of experience in Data Science or Machine Learning, with a strong focus on tabular ML.
• Strong understanding of gradient boosting and hands-on experience with CatBoost, LightGBM, or XGBoost.
• Strong Python skills with Pandas, NumPy, and Scikit-learn.
• Advanced SQL skills and experience with ClickHouse or other column-oriented databases.
• Hands-on experience with Airflow and production-ready DAGs.
• Understanding of validation techniques such as Group Split and Time-series Split, data leakage prevention, and model explainability with SHAP or LIME.

Nice to have

• Experience in iGaming, betting, e-commerce, or fintech.
• Understanding of LTV, CPA, retention, cohort analysis, and other marketing metrics.
• Experience building uplift, attribution, or churn prediction models.

Culture & Benefits

• Flexible remote or office-based work format.
• Scalable projects and products used by millions.
• Engineering culture with no micromanagement.
• Relocation support and competitive compensation.
• Reimbursement for sports, professional education, language courses, mental health support, and medical services.
• Continuous learning, knowledge sharing, and professional growth.