• Build and lead a high-performing data science team, fostering collaboration and innovation. • Mentor and guide team members on technical and strategic initiatives. • Design and implement advanced machine learning models for fraud detection, risk scoring, and acceptance optimization. • Collaborate with engineering and risk teams to integrate models into production systems. • Define and execute a scalable data science strategy that aligns with Conekta's business objectives. • Develop frameworks for data collection, feature engineering, and real-time model deployment. • Analyze large-scale payment data to identify trends, anomalies, and areas for improvement in payment success rates. • Develop predictive models to enhance payment authorization rates and reduce transaction declines. • Continuously refine fraud detection models to address emerging threats and new fraud patterns. • Partner with product, engineering, and business teams to align data science initiatives with company goals. • Communicate complex findings and insights to non-technical stakeholders effectively

• Direct impact on the business and its growth • Working directly with the CEO and play as a key analytics partner • Ability to expand and scale the team • Building analytics for the most challenging periods and cases • Team management, including hiring new teammates

• lead the biostatistics, data management, and statistical programming functions across all clinical programs • serve as a core member of the clinical development leadership team, contributing to portfolio strategy, asset prioritization, and program governance • provide statistical leadership for oncology trial design, including adaptive designs, Bayesian approaches, biomarker-driven studies, and complex endpoints (e.g., OS, PFS, ORR, MRD) • guide development strategies from first-in-human through registrational and post-marketing studies • act as the statistical authority in interactions with global regulatory agencies (FDA, EMA, PMDA, etc.) • oversee the statistical and data components of INDs, NDAs, BLAs, MAAs, and responses to regulatory questions • ensure timely, high-quality delivery of statistical analyses, datasets, TFLs, and clinical study reports • oversee CRO and vendor strategy for data management and programming • establish scalable processes, standards, and infrastructure to support a growing oncology pipeline • drive innovation in data review, analytics, and visualization to enable real-time decision-making • build, mentor, and retain a high-performing, multidisciplinary team across biostatistics, data management, and statistical programming • partner closely with Clinical Development, Clinical Operations, Regulatory Affairs, Translational Medicine, Medical Affairs, and Commercial teams.

• Apply statistical and machine learning techniques to solve quantitative problems in the insurance industry • Expand your skills with hands-on training and mentorship from seasoned data scientists • Improve upon quantitative solutions in Claims, Lifetime Value Estimation, or Marketing • Communicate insights from complex analyses to technical and non-technical audiences • Present findings to leaders and stakeholders, showcasing the value of your work • Demonstrate proficiency in data science fundamentals by the end of the program, with the potential to transition into a full-time Data Scientist role