1886515157 Remoto Remoto We are looking for a Senior Data Science Consultant who will be responsible for identifying, designing, and leading advanced analytical initiatives that optimize operational processes, improve customer experience, increase revenue (sales and collections), and generate efficiencies in Contact Center and BPO services. This role will combine both technical and business skills. Key responsibilities: Lead the design and execution of advanced analytical solutions with direct impact on sales, collections, operational efficiency, and customer experience. Identify high-value opportunities for developing predictive and prescriptive models. Validate the technical feasibility of initiatives and coordinate their implementation with engineering and security teams. Communicate findings and recommendations to senior stakeholders, translating technical insights into strategic decisions. Serve as a technical reference and mentor for other analysts and data scientists. Design experiments and A/B tests to validate business hypotheses and measure the impact of proposed solutions. Ensure best practices in managing the model lifecycle: from development to monitoring and recalibration. Document solutions clearly and structurally to facilitate reuse and maintenance. Stay updated on emerging trends and tools in data science, artificial intelligence, and machine learning. Qualifications: University degree in Engineering, Statistics, Economics, or related fields. Graduate studies (specialization or master's) in Analytics will be positively valued. Over 5 years of experience leading data science projects in complex, high-volume data environments. English level B2. Programming languages: Python, R, SQL. Data visualization tools: Power BI, Tableau. Cloud platforms: AWS, Azure, or Google Cloud Platform (GCP). Databases and storage: Snowflake, relational and non-relational databases. Machine Learning and Predictive Modeling: development, training, and validation of supervised and unsupervised models. Natural Language Processing (NLP) and text analysis. Basic knowledge of data engineering: data integration, transformation (ETL/ELT), handling large volumes of data. Consumption and design of APIs for integrating models and analytical solutions. We are looking for a Senior Data Science Consultant who will be responsible for identifying, designing, and leading advanced analytical initiatives that optimize operational processes, improve customer experience, increase revenue (sales and collections), and generate efficiencies in Contact Center and BPO services. This role will combine both technical and business skills. Key responsibilities: Lead the design and execution of advanced analytical solutions with direct impact on sales, collections, operational efficiency, and customer experience. Identify high-value opportunities for developing predictive and prescriptive models. Validate the technical feasibility of initiatives and coordinate their implementation with engineering and security teams. Communicate findings and recommendations to senior stakeholders, translating technical insights into strategic decisions. Serve as a technical reference and mentor for other analysts and data scientists. Design experiments and A/B tests to validate business hypotheses and measure the impact of proposed solutions. Ensure best practices in managing the model lifecycle: from development to monitoring and recalibration. Document solutions clearly and structurally to facilitate reuse and maintenance. Stay updated on emerging trends and tools in data science, artificial intelligence, and machine learning. Qualifications: University degree in Engineering, Statistics, Economics, or related fields. Graduate studies (specialization or master's) in Analytics will be positively valued. Over 5 years of experience leading data science projects in complex, high-volume data environments. English level B2. Programming languages: Python, R, SQL. Data visualization tools: Power BI, Tableau. Cloud platforms: AWS, Azure, or Google Cloud Platform (GCP). Databases and storage: Snowflake, relational and non-relational databases. Machine Learning and Predictive Modeling: development, training, and validation of supervised and unsupervised models. Natural Language Processing (NLP) and text analysis. Basic knowledge of data engineering: data integration, transformation (ETL/ELT), handling large volumes of data. Consumption and design of APIs for integrating models and analytical solutions. Profesional Especialización Ingeniería de sistemas Computación Ingenierìa De Software 5 años de experiencia 1Vacante #J-18808-Ljbffr