Assistant Director Data Science - DSS

We are building a global Data Science hub in Colombia and are seeking an Assistant Director, Data Science, a visionary leader to collaborate in building this new organization. This is a hybrid technical and people-leadership role. The Assistant Director will be responsible for leading complex Data Science and model automation initiatives, building strong partnerships with global technical and business teams, and developing Data Science talent within the Bogotá hub. The Assistant Director will have direct reports and will be accountable for coaching, developing, and managing junior and mid-level Data Scientists and Analysts. This role will also contribute to the growth, operating model, and long-term capabilities of the Colombia Data Science organization. In this pivotal role, you will: Own complex Data Science initiatives from problem definition and solution design through deployment support, monitoring, and ongoing enhancement. Translate business objectives into clear analytical strategies, technical roadmaps, delivery plans, and measurable outcomes. Serve as a senior technical advisor to Data Science teams, business partners, engineering teams, and organizational leadership. Challenge assumptions, technical approaches, and analytical conclusions to ensure quality, rigor, and business relevance. Lead technical reviews, code reviews, model reviews, and knowledge-sharing forums. Scale a high-performing team of data science professionals. Collaborate on recruitment efforts, identifying and attracting top-tier talent. Mentor and develop junior team members, fostering a culture of continuous learning and innovation. Drive strategic outcomes, ensuring the team’s work aligns with and advances key business objectives. We're looking for a leader who is not only technically strong in data science and analytics but also passionate about building teams, shaping culture, and delivering measurable business value. Key Responsibilities: Build and lead a new team of data science professionals, fostering a high-performance culture rooted in collaboration, innovation, and continuous improvement. Design and implement scalable model operations, including monitoring, refreshing cycles, and performance enhancements to ensure long-term model reliability and business impact. Develop and automate machine learning pipelines that streamline model development and model deployment. Apply advanced analytics and modeling techniques to large, complex datasets to generate actionable insights and predictive solutions. Translate complex quantitative findings into clear, compelling narratives and visualizations for technical and non-technical stakeholders. Mentor and develop junior team members, providing technical guidance and fostering a culture of learning and knowledge sharing. Drive innovation by staying current with emerging tools, technologies, and methodologies in the data science and MLOps space. Contribute to cross-functional initiatives, representing the Colombia hub and shaping the future of data science operations across the organization. Skills and Experience: Fluency in English C1 (Must) Collaborate effectively within the Colombia location and global teams Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, Actuarial Science, or a related quantitative field. A master's degree is preferred, or equivalent to industry experience. 7-8+ years of professional experience in Data Science, Machine Learning, Advanced Analytics, or a related field. Proven leadership experience in high-performing data science or analytics teams, ideally in a global or distributed environment. Strong technical expertise in applied machine learning, statistical modeling, and data engineering, with hands-on experience in model development, deployment, and lifecycle management. Proficiency in programming languages such as Python, SQL, and experience with cloud platforms (e.g., AWS, Azure, GCP) and data tools (e.g., Spark, Airflow, MLflow). Experience working with GenIA pipelines and being able to talk about best standars. Strong experience with Git and GitHub, including branching strategies, pull requests, code reviews, and collaborative development practices. Excellent problem-solving skills, with the ability to translate complex business challenges into data-driven solutions. Strong communication and stakeholder management skills, with the ability to influence and collaborate across technical and non-technical teams. Experienced in delivering training, mentoring, and knowledge-sharing sessions to elevate team capabilities and promote best practices. Experience in insurance or financial services is highly desirable, particularly in regulated environments or with high-impact modeling use cases. Curious about emerging Data Science, MLOps, software engineering, and Generative AI practices and evaluating their relevance to the organization. Highly desirable / nice to have Experience with Generative AI / LLMs (prompt engineering, vector embeddings, RAG, evaluation and mitigation strategies for hallucinations). Familiarity with MLflow or similar experiments and model tracking systems. Experience implementing model monitoring, feature/label drift detection, and automated retraining pipelines. Knowledge of actuarial/insurance modeling concepts and domain experience. #J-18808-Ljbffr