Idriss Olivier Bado

– Define and execute the enterprise-wide data strategy across payments, mobile money, and financial services, enabling secure and scalable processing of 2M+ daily transactions in France, Ivory Coast, Senegal, Morocco markets. – Provide executive leadership in data governance, AI/ML innovation, and digital transformation, embedding advanced analytics into core business operations to accelerate growth and mitigate systemic risks. – Drive measurable business impact by institutionalizing experimentation frameworks (Python/SQL A/B testing), directly contributing to a 20% uplift in retention and customer lifetime value. – Oversee the cloud modernization roadmap, steering large-scale migration of analytics pipelines to Microsoft Azure, delivering a 35% improvement in query performance while reducing operating costs. – Establish real-time data intelligence platforms (Power BI, Elasticsearch) that strengthen fraud detection, enhance decision-making, and provide actionable insights to the Board and executive committees. – Act as a strategic advisor to senior leadership, aligning data initiatives with corporate objectives, regulatory compliance, and market expansion across Africa and Europe.

– Designed and delivered graduate-level courses in stochastic processes with cross-disciplinary applications in finance, engineering, econometrics, and artificial intelligence, equipping students with advanced modeling and analytical capabilities. – Delivered in-depth instruction on Poisson, Markov, Gaussian, and Wiener processes, enabling learners to apply probabilistic and statistical frameworks to real-world systems. – Introduced advanced mathematical concepts including ergodicity, stationarity, and stochastic integration, providing the foundation for quantitative finance, stochastic calculus, and jump-type process modeling. – Guided students in applying stochastic frameworks to financial markets, econometric modeling, and risk analysis, bridging theory with practical impact. – Strengthened the university's academic reputation in applied mathematics and AI by fostering research excellence, designing industry-aligned curricula, and mentoring future leaders in data-driven finance and engineering.

– Designed and delivered graduate-level courses in time series analysis with applications in economics, data science, and predictive forecasting, preparing students for leadership roles in quantitative research and analytics. – Taught advanced methodologies including decomposition techniques, seasonal adjustment, exponential smoothing, AR/MA/ARMA models, Box-Jenkins methodology, and unit root testing, equipping learners with industry-standard forecasting tools. – Introduced multivariate modeling techniques such as cointegration, VECM, and VAR models, enabling students to analyze complex economic and financial systems. – Supervised applied forecasting projects leveraging real-world datasets, guiding the development of interactive R Shiny dashboards that connected academic theory with practical business applications. – Strengthened institutional capacity in quantitative economics, statistical modeling, and machine learning for forecasting, advancing CNAM's reputation as a regional leader in data-driven education and applied econometrics.

– Architected and institutionalized Monitoring, Evaluation, and Learning (MEL) systems across (West & East Africa, India) 10+ regional programs, enhancing data accuracy, reporting efficiency, and decision-making timelines for donor-funded initiatives. – Pioneered the integration of geospatial analytics, machine learning, and predictive modeling to forecast program outcomes, delivering real-time impact visualization for executive leadership and external stakeholders. – Directed the design of strategic logframes, KPI dashboards, and geodata pipelines leveraging Python, R, Power BI, and QGIS, driving evidence-based program design and resource allocation. – Championed a data-driven culture, embedding MEL frameworks into organizational strategy, ensuring compliance with international donor standards (USAID, DFID, World Bank), and positioning programs for sustainable scaling. – Partnered with cross-regional leadership to align MEL innovation with corporate priorities, funding objectives, and ESG imperatives, strengthening TechnoServe's reputation as a global leader in impact-driven development.

– Directed the design and deployment of supervised machine learning models for fraud detection and risk mitigation, reducing detection time by 30% and strengthening enterprise-wide resilience. – Orchestrated advanced experimentation frameworks to validate business hypotheses, optimize model performance, and accelerate data-to-decision cycles for senior leadership. – Championed the implementation of time series forecasting and spatial analytics, driving cost optimization, operational efficiency, and predictive accuracy across multiple business units. – Spearheaded cross-functional collaboration between data science, risk management, and product teams, embedding AI-driven decision intelligence into corporate strategy and client solutions. – Elevated organizational data science maturity by standardizing methodologies, mentoring teams, and institutionalizing best practices in model governance, ethical AI, and explainability. – Served as a trusted advisor to executives and regulators, ensuring data-driven risk models met compliance standards while enabling innovation at scale.

– Modeled stochastic systems and engineered optimization algorithms, delivering high-performance solutions that improved efficiency, risk management, and decision-making for consulting clients across finance and technology sectors. – Directed theoretical research and practical implementation of complex mathematical and computational frameworks, bridging advanced research with real-world business applications. – Collaborated with executive stakeholders to translate research outputs into scalable, data-driven strategies aligned with client growth and digital transformation agendas. – Published and presented findings in technical and client-facing contexts, reinforcing Kyria's reputation as a trusted partner in innovation, applied mathematics, and algorithmic engineering.

– Directed end-to-end market research programs across multiple industries, from project design and data collection to advanced analytics and final delivery, influencing executive decision-making and digital transformation strategies. – Engineered and executed A/B testing frameworks, customer segmentation models, CLV modeling, and funnel optimization, boosting client acquisition, retention, and revenue growth. – Leveraged real-time metrics, predictive analytics, and cohort analysis to provide actionable insights, guiding clients in digital strategy, customer experience optimization, and market expansion. – Collaborated with senior stakeholders to translate research outputs into data-driven strategies that aligned with evolving business objectives and competitive landscapes.

– Delivered advanced instruction in spatial data analysis, programming, and applied machine learning, equipping graduate students with the tools to tackle real-world geospatial and AI-driven challenges. – Supervised applied research projects in survey methodology, spatial econometrics, and predictive analytics, enabling students to translate theory into actionable insights for policy, urban planning, and business intelligence. – Integrated open-source platforms, Python libraries, and GIS technologies into course design, ensuring graduates were prepared for careers in data science, geospatial analytics, and AI innovation.

– Engineered enterprise-grade data warehouses, ETL pipelines, and analytics dashboards for financial institutions and public sector organizations, enabling real-time decision intelligence and regulatory compliance. – Designed and deployed advanced algorithms and machine learning models to optimize pricing strategies, investment scenarios, and risk management, driving measurable improvements in profitability and portfolio performance. – Directed data architecture modernization projects, standardizing infrastructure to support business intelligence, predictive analytics, and digital transformation initiatives. – Partnered with senior executives and government stakeholders to translate complex data ecosystems into actionable insights, influencing policy decisions and corporate strategy. – Championed data governance, security, and scalability frameworks, ensuring alignment with financial regulations, international standards, and organizational growth objectives. – Elevated consulting impact by integrating cloud-based solutions (Azure, AWS, GCP) and modern data platforms, positioning clients for long-term digital and analytics maturity.

– Engineered and deployed secure RESTful APIs powering pricing engines for insurance and actuarial applications, enhancing accuracy, scalability, and compliance in premium calculations. – Optimized data integration pipelines to support risk modeling, underwriting automation, and actuarial reporting, reducing manual intervention and accelerating decision-making cycles. – Applied enterprise-grade security protocols to safeguard sensitive financial data and align with regulatory requirements in the insurance sector. – Partnered with cross-functional actuarial and IT teams to translate complex risk models into efficient, production-ready systems that improved customer experience and operational efficiency.

– Conducted expert peer reviews of academic manuscripts and international conference submissions in artificial intelligence, algorithms, and computational sciences, ensuring research met global standards of rigor and innovation. – Evaluated contributions on machine learning, optimization, and advanced computing methodologies, providing constructive feedback that strengthened the quality and impact of published research. – Collaborated with an international network of scholars and practitioners, contributing to the advancement of cutting-edge AI applications and algorithmic developments across academia and industry.

– Supported macroeconomic and trade policy analysis by applying applied econometrics and advanced Excel modeling, enhancing data-driven insights for executive decision-making. – Conducted market research and sectoral studies that informed the Chamber's strategic reports on foreign trade, investment flows, and economic competitiveness. – Contributed to the design of evidence-based policy briefs and analytical dashboards, strengthening the Chamber's role as a key advisor to government, private sector stakeholders, and international partners.