Data Science Coordinator

Description

Job Summary: The Data Science Coordinator aligns expectations across departments, structures analytical requests, manages priorities, and promotes a data-driven culture within the organization. Key Highlights: 1. Guide data scientists, support technical development, and remove blockers. 2. Define the analytical backlog with business teams and align deliveries. 3. Promote a data-driven culture and enhance the organization's analytical maturity. Description: Education: * Bachelor's degree in quantitative fields (mathematics, physics, statistics, or engineering), economics, or computer science. * Preferred: Postgraduate degree, MBA, or specialization in Data Science, Data Engineering / MLOps, and/or Artificial Intelligence. Technical Skills: * Statistics, modeling, and machine learning. * Programming (Python/R) and cloud tools (AWS, GCP, or Azure). * SQL, databases, pipelines, and foundational data engineering concepts. * MLOps, model monitoring, and versioning. * Data visualization and data storytelling. The Data Science Coordinator faces key challenges including aligning expectations between technical and business teams, transforming ill-defined requests into clear and feasible analytical scopes, rigorously managing priorities, and balancing delivery speed with technical quality. Additionally, they must maintain clear communication with diverse stakeholders and actively promote a data-driven culture—demonstrating impact and contributing to the organization's analytical maturity evolution. Key Responsibilities: * Guide data scientists at various seniority levels, support their technical development, define priorities, and remove blockers. * Define and prioritize the analytical backlog with business teams, assess feasibility, and align expectations and deliveries. * Ensure best practices in modeling, metrics, versioning, testing, documentation, and governance. * Translate business problems into analytical hypotheses and solutions, presenting results clearly and value-oriented. * Facilitate ceremonies, schedules, and alignment among engineering, product, IT, business, and data teams. * Ensure operationalization and continuous monitoring of production models, guaranteeing performance and reliability. * Foster best practices and support the organization's analytical maturity by promoting education, alignment, and responsible data usage. * Assist in mentoring and developing less experienced team members. 2512100202181911634