Horas de trabajo
Full time
Ubicación
Cualquier lugar
Lugar de trabajo
Remoto
Tipo de contrato
Contrato indefinido
What is Cobre and what do we do?
Cobre is Latin America’s leading instant b2b payments platform. We solve the region’s most complex money movement challenges by building advanced financial infrastructure that enables companies to move money faster, safer, and more efficiently.
We enable instant business payments—local or international, direct or via API—all from a single platform.
Built for fintechs, PSPs, banks, and finance teams that demand speed, control, and efficiency. From real-time payments to automated treasury, we turn complex financial processes into simple experiences.
Cobre is the first platform in Colombia to enable companies to pay both banked and unbanked beneficiaries within the same payment cycle and through a single interface.
We are building the enterprise payments infrastructure of Latin America!
What we are looking for
Join Cobre as a Senior Data Scientist, AML, reporting to the Head of Data and Decisioning. This critical role sits at the intersection of data science and financial technology, helping to drive the fintech industry forward. As a key player in our Risk Products squad, you will develop and implement advanced analytical solutions tailored to the needs of our Compliance and Risk teams.
Your role will require a blend of deep technical expertise and innovative thinking, pushing the boundaries of predictive analytics and applying it to areas such as financial risk management and fraud detection. You will play a pivotal role in shaping our data strategies, transforming complex data challenges into scalable solutions. Your work will contribute to defining the future of data science at Cobre and making a significant impact on the fintech sector.
What would you be doing
Applied Data Science: Develop and implement advanced AI, ML models and algorithms using mathematical concepts to create analytics solutions to enhance our AML Transaction Monitoring, Sanctions Screening and Due diligence. Utilize techniques such as anomaly detection, clustering, and classification.
Data Strategy Implementation: Align data science initiatives with Cobre's goals, incorporating predictive modeling and quantitative analysis to enhance our capabilities. Identify infrastructure needs to integrate these models and algorithms into our platform.
Innovation through AI: explore new AI solutions and techniques that can impact and add value to our internal Risk teams and our clients.
Technical excellence: Stay abreast of trends in data science, focusing on the mathematical foundations. Ensure best practices in model development, deployment, and governance.
Collaborative Projects: Work with Compliance and other Risk teams to support their functions with rigorous mathematical analysis.
Stakeholder Engagement: Understand stakeholder needs, prioritize projects, and deliver impactful data-driven solutions.
Mentorship and Development: Assist in mentoring junior data scientists, fostering a culture of continuous learning and improvement.
What do you need
Experience: 5+ years in data science with a strong understanding of machine learning techniques and algorithms. Hands-on experience building predictive models, preferably in the financial industry or consulting.
Education: Bachelor’s or Master’s degree in a quantitative field such as Mathematics, Statistics, or a related discipline.
Technical Skills: Proficiency in Python, SQL, and machine learning libraries such as TensorFlow. Experience with data visualization tools (e.g., Tableau), cloud platforms (e.g., AWS), and data warehousing solutions (e.g., Snowflake) is highly desirable.
Financial Crimes: Experience in business analytics, risk management, anti money laundering and fraud detection.
Collaboration: Strong ability to work across departments and foster a collaborative environment.
Communication Skills: Excellent communication and collaboration skills, with the ability to effectively convey complex technical concepts to non-technical stakeholders. Being bilingual in English and Spanish is a must.