Translate business objectives into clear data science problems with measurable success criteria

Explore, clean, and integrate complex datasets while engineering high-impact features

Build, validate, and refine predictive, classification, ranking, NLP, and time-series models

Design and analyze experiments including A/B and multi-arm tests for reliable causal inference

Communicate insights effectively through narratives, visualizations, and actionable recommendations

Collaborate with product and engineering teams to deploy and monitor machine learning models in production

Develop and maintain scalable dashboards and reporting systems to facilitate real-time business monitoring

Architect and optimize data pipelines for large-scale data ingestion, transformation, and integration

Define, implement, and track success metrics for AI-driven features and digital transformation efforts

Partner with stakeholders to translate data insights into strategic business recommendations

Extensive applied data science experience of 3+ years in production environments

Strong foundation in statistics, probability theory, and experimental design

Advanced proficiency in SQL and at least one general-purpose programming language with experience in machine learning libraries

Experience handling large datasets and familiarity with distributed data processing frameworks

Expertise in model evaluation, validation, and monitoring using offline and online metrics

Fluency in data visualization and delivering executive-level communications

Knowledge of MLOps practices and collaboration with data and platform engineering teams

Bachelor's or Master's degree in a quantitative field or equivalent experience

Upper-Intermediate English language proficiency (B2)

Experience with natural language processing, forecasting, recommendations, or anomaly detection

Familiarity with causal inference and A/B testing methodologies

Hands-on experience with feature stores, real-time data processing, or online machine learning systems

Knowledge of cloud data platforms and modern data warehouses

Mentoring experience and contributions to cross-team projects