We are seeking a **Senior Data Scientist** to transform complex data into actionable insights and machine learning products that drive significant business impact. You will collaborate with product and engineering teams to frame problems, develop models, and deliver clear data narratives. Join us to leverage your expertise in dashboarding tools and cloud data platforms to shape strategic decisions and innovation. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi\-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting\-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential. **Responsibilities** * 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 **Requirements** * 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\) **Nice to have** * 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 **We offer** * Connectivity Bonus (25,000 ARS are paid with a salary receipt at the end of each month as a non\-wages concept). * Medicina Prepaga (It covers the collaborator and direct family group). * Paternity Leave (Two additional days are added to what is established by law, total of 4 days). * Discounts card. * English Training (English lessons, twice per week). * Training Program (Access to multiple customized training plans according to the needs of each role within the company). * Marriage bonus (The company doubles the allowance established by law that ANSES offers). * Referral Program (Referral bonus is paid when the referral of a collaborator joins the Company). * External Agreements and Discounts. * Vacations: 14 calendar days a year *By applying to our role, you are agreeing that your personal data may be used as in set out in EPAM´s Privacy Notice and Policy.*