Head Of Analytics jobs in Mexico
Data Science and Analytics Lead
Research And Analytics Manager
Manager, Digital & Analytics Solutions
Data Science and Analytics Lead
Manager - Product Analytics - eCommerce
Manager, Digital & Analytics Solutions
Sales Analytics Manager
VIE - Business planning & analysis coordinator (M / W)
Connect with headhunters to apply for similar jobsManager - Consumer Insights & Analytics
Manager, Digital & Analytics Solutions
Commercial Analytics Manager
Manager - Business Analytics - Dubai Holding Real Estate
Manager - Retail Analytics
Commercial Analytics Manager
Data Analytics Lead
Data Analytics Lead | Group Technology | Corporate Services
Data Analytics Specialist
Data Analysis Manager
Manager - Business Analytics - Dubai Holding Real Estate
Product Analytics Manager
Product Analytics Manager
Regulatory Analytics Manager
Data Science and Analytics Lead
We represent a technology player whose digital banking platform is transforming financial services in emerging markets making a real impact by embedding credit and savings products into the digital channels people use every day. Their data-driven technology powers MNOs, fintechs, and banks enabling them to scale fast and drive financial inclusion for millions. For those looking to work on cutting-edge financial tech with real-world impact, this is the opportunity for you. With rapid growth, industry recognition, and a team that thrives on innovation, this is a chance to shape the future of finance in high-growth markets across Africa.
Job Description:
The Data Science and Analytics Lead will enhance their credit risk modelling, predictive analytics, and operational efficiency. Improve multi-source data integration, strengthening model governance, automating data processes, and scaling our infrastructure for faster decision-making and market expansion. The Data Science and Analytics Lead will drive data-driven insights, refine risk models, and build scalable solutions that optimize lending decisions and business growth.
Your daily adventures include:
Strategic Leadership & Business Impact
- Drive the development of the data science strategy to support business growth, embedded finance, and new market expansion.
- Leverage AI and behavioral science insights to enhance credit performance, customer engagement, and savings adoption.
- Partner with product, risk, and engineering teams to integrate data science into decision-making and operational processes.
Model Development & AI Governance
- Build, refine, and deploy AI-powered credit scoring models ensuring high performance, fairness, and explainability.
- Lead experimentation and A/B testing initiatives to enhance underwriting, portfolio management, and product innovation.
Data Infrastructure & Scalability
- Collaborate with Engineering to expand data science capabilities to support multiple markets, optimizing for scalability and adaptability.
- Ensure data integrity, security, and compliance across all data science initiatives.
Team Leadership & Development
- Drive best practices in model development, MLOps, and responsible AI.
- Promote cross-functional collaboration to maximize the value of data science across the organization.
Requirements
What it takes to succeed:
- Strong background in data science, machine learning, and AI with experience in credit risk modelling and financial services.
- Deep understanding of AI governance, model transparency, and regulatory compliance in financial services.
- Hands-on experience with MLOps, model deployment, and automated monitoring solutions.
- Strong analytical mindset with a proven ability to drive business impact through data science.
- Excellent leadership skills with the ability to mentor and build high-performing teams.
- Bachelor's degree in a quantitative field such as Statistics, Mathematics, Physics, Computer Science, Data Science, Engineering, Economics, Financial Engineering, Actuarial Science, or a related discipline.
- Experience in fintech, digital lending, or embedded finance is preferred.
- Exposure to cloud platforms such as AWS, GCP, or Azure for data engineering and machine learning is beneficial.
- Familiarity with graph analytics, network science, or behavioral data modelling is beneficial.
- Knowledge of causal inference techniques and advanced experimentation methodologies is beneficial.
- Prior experience in expanding data science functions into new markets is beneficial.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.
job faster
