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Would you like to help us achieve our purpose of connecting more people, improve their lives and develop our communities? If so, Tigo is for you!We believe in innovation, we adapt and are agents of change. Our customers are at the center of everything we do.Come and grow with our team, where together we will transform lives and communities. Additionally, you will have the opportunity to participate in challenging projects and bring your innovative ideas.This is your opportunity, come and be part of Sangre Tigo!Apply right now!Credit Risk Data ScientistKey responsibilitiesThis position will assist the Risk & Fraud Team in managing the various information systems and databases, interacting closely with managers within the Risk department and other internal departments for operational purposes.Collaborates with analytics and business teams to research, design, prototype, test and document scoring models using advance analytics for automated, near real time decision making.Validates periodically performance indicators of scoring models used by lending processesPropose new analytical tools to support lending decision making processCollaborates with analytics, data engineering and business teams to improve data models that feed MFS' Data Lakehouse, increasing data accessibility and fostering data-driven decision making across the organization.Designs and implements processes and systems for performing tasks such as data cleansing, exploratory analysis, predictive modeling (including rules engines), and analytics operations once the model is release into production.Test model output through back testing, sensitivity analysis, stress testing or other analysis as applicableDevelop, review and enhance the internal PD, LGD and EAD/CCF credit risk models in accordance with internal standards and best practicesPresents findings to teammates and guide the transition of new algorithms into operational code.Also serves as a point person for collaborations with various stakeholders including subject matter experts, business owners, business analysts, software engineers, data engineers, and upper management.Desired Professional ExperienceAt least 3+ years experience at lending institutions.Strategic thinker with strong analytical and creative problem-solving skills. Conducts extensive research, identifies business problems and creates analytical/modeling frameworks and solutions.Experience working with Credit Reference Agency data.Prior experience developing and validating credit risk scores. Experience implementing experimental design or Champion – Challenger strategiesSolid knowledge in: Programming languages (Python, R , SAS), Machine Learning packages (scikit-learn, Tensorflow, Pytorch), Supervised Learning and Unsupervised Learning ML, Data visualization tools (Tableau or Power BI) and ideally AI Platforms (Datarobot, Sagemaker, H2O.ai)Additional qualifications: advanced SQL knowledge is required (No-SQL experience is a plus)DesiredEducationProfileBachelor's Degree in quantitative discipline such as Financial Engineering, Computational Finance, Mathematical Finance, Math/Statistics, Econometrics, or related fields.We are a leading multinational company of mobile services, internet and cable television that is present in Latin America and we are the leading telecommunications company in Panama. In Latin America, Tigo has been recognized for several years in the "Great Place to Work" ranking as an excellent company to work for.
Our people are our most precious asset. Tigo Panama directly employs more than 2,500 people nationwide and offers internal growth opportunities to its staff. We have a firm purpose that moves us and unites all of us who work in the company: "To build the largest digital network to connect Panamanians by developing the communities we serve and improving their quality of life." Sangre Tigo runs through our veins, we are proud of our company and its history, we are innovative, we are passionate, we live to improve our communities and our clients are at the center of everything we do. We invite you to be part of our Tigo family!
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