• Define and execute the analytical framework for evaluating agent and channel performance across a multichannel distribution model • Design and implement predictive models supporting growth opportunity identification, customer experience, retention risk, and channel optimization • Conduct program evaluation using experimental and quasi-experimental methods to establish causal impact of business initiatives • Translate analytical findings into clear, actionable recommendations for senior leadership • Set and prioritize the analytical agenda independently, focusing on the highest-value questions • Operate effectively in a data environment that is not fully controlled or curated, maintaining rigor despite imperfect inputs

• Directly manage a team of highly skilled data scientists. Start from 2-3 and grow to 5-6. • Act as a technical mentor that can dive deep and provide detailed direction. • Lead planning, resourcing and communications with senior leadership, product and engineering teams. • Develop strong business intuition and guide your team to deliver performant DS solutions on aggressive timelines. • Develop and maintain SentiLink’s fraud detection models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring. • Research new types of fraud and develop new SentiLink products around identity verification. • Achieve success by researching / developing through iteration, integration of new data sources and inventive feature engineering. • Write production-ready code that can be relied on for real-time decision making by our partners. • Design, perform, and present analyses that will inform data acquisition, product development, risk operations priorities, marketing, and sales efforts.

Role Description The Clinical Data Manager (CDM) handles project management documentation, clinical data management activities, and system implementations for EDETEK’s eClinical, and may be assigned work on other platforms. This includes writing design specifications for the system (forms, reports, etc.) and facilitating testing of system implementations. The CDM is responsible for all other traditional clinical data management operations and activities such as: - Facilitating database audits - Coding - SAE reconciliation - System and module testing - Data cleaning - Locking and unlocking of clinical databases The CDM is responsible for translating the client’s Clinical Data Management requirements and expectations into DMP and implementing the clinical data management plans so that the clients’ expectations are met. The CDM is responsible for the quality and integrity of the data in the final locked clinical database. The CDM should thoroughly understand the requirements for Good Clinical Data Management services, including its documentation; be willing to be involved in start-up or wrap-up of in-house and client-specific data management projects; have an understanding of the relevant therapeutic indications, study hypotheses, and trial design; and have a solid understanding of database design and structure. Qualifications - Ability to communicate effectively in the English language in person, by phone and in writing. - Ability to lead functional meetings. - Strong attention to detail and accuracy is a must. - Excellent organizational skills. - Demonstrated ability to manage multiple projects. - Ability to work collaboratively, effectively, and productively in diverse organization structures. - Ability to work independently, take initiative and complete tasks to deadlines. - Ability to work in a team-oriented, collaborative environment. - Ability to work positively within a continually changing environment. - Ability to effectively prioritize and execute tasks in a high-pressure environment. - Advanced computer skills and practical knowledge of MS Office and potentially project management software. Requirements - A Bachelor’s degree or equivalent combination of Education/Training/Experience is required. - A degree in a scientific, medical, or technological discipline is preferred. - A minimum of 2 years of clinical trial or clinical data management experience or similar industry experience/training is required. - Prior trial responsibility for the entire data management life-cycle is desirable. - Working knowledge of EDC studies and SAS is required. Benefits - Choice of comprehensive Medical, Vision and Dental Insurance plans. - Paid vacation time and sick days. - Corporate holidays annually. - Participation in the 401K Plan. - Comprehensive perks and discount programs for AAA, wholesale, insurance, Rx, fitness, pets, entertainment, etc. - Health Advocate and Employee Assistance Program. Location This is a remote position, and we are open to candidates based in the United States and South America. Equal Opportunity Employer Statement EDETEK is an equal opportunity employer and does not unlawfully discriminate against employees or applicants for employment on the basis of an individual’s race, color, religion, creed, sex, national origin, age, disability, marital status, veteran status or any other status protected by applicable law. This policy applies to all terms, conditions and privileges of employment, including recruitment, hiring, placement, compensation, promotion, discipline, and termination. Whenever possible, the company makes reasonable accommodations for qualified individuals with disabilities to the extent required by law.

• Design, develop and deploy advanced statistical or machine learning models for credit risk, pricing, collections, fraud, and other high-impact business use cases that drive better data-driven decisions • Lead end-to-end delivery of data science initiatives from problem framing and model design through deployment, monitoring and ongoing maintenance • Partner with cross-functional teams including Portfolio Strategy, Engineering, Product, Underwriting, Sales and Collections to integrate models into our applications, and proactively identify and solve problems in critical business areas • Define and set standards for model development, code quality, and documentation; guide technical design decisions across the team • Act as a technical mentor to team members, fostering a culture of continuous learning and rigorous analytical standards • Communicate complex technical concepts and business implications to both technical and non-technical stakeholders • Build and maintain production machine learning pipelines and monitoring systems to ensure models are reliable, scalable and continuously improving