Experience

GainX

• Canada
• Software Development
• 1 - 100 Employee

• Data Scientist - Research and Advanced Analytics

  • Dec 2021 - Present

  Conduct in-depth research to identify solutions for business and customer challenges. Leverage advanced ML algorithms, cloud computing, and AI-based solutions to formulate hypotheses and functional prototypes for validating and implementing innovative data-driven strategies. Collaborate with university researchers to integrate cutting-edge findings from various disciplines, ensuring we stay at the forefront of data science. Key Achievements: • Engineered smart algorithms/applications to predict project failures (budget, end date, and benefit) with 98% accuracy through the development of advanced machine learning models, resulting in enhanced project management success. • Created data-driven solutions to predict strategic alignment between people, projects, and initiatives with high accuracy using deep learning models (Transformers and social network analysis), significantly contributing to the achievement of organizational goals. • Designed Artificial Intelligence-driven solutions to predict Network Health within and around groups of people by utilizing probabilistic deep learning models (Bayesian Network, Social Network Analysis, and Transformers), providing valuable insights for improving key performance indicators. • Developed AI-based solutions to predict workplace distractions using advanced analytics (Transformers, Bayesian Gaussian Mixture, and Bayesian Network), resulting in effective management of attention overload situations. • Designed a versatile machine learning framework for building smart indicators with high-level properties, including self-construction and knowledge accumulation, leading to faster and streamlined decision-making across industries and enhanced operational efficiency. • Produced deep learning-enabled solutions for transforming unstructured data on people, projects, and initiatives into machine learning features across industries using a framework based on Transformers and topic modelling. Show less



Collège Boréal

• Canada
• Higher Education
• 300 - 400 Employee

• Professor

  • Jan 2020 - Dec 2021

  Instructed diverse computer science and applied mathematics courses for data science, nurturing students' skills and proficiency in the subject. Conducted research and developed numerous machine learning models to tackle industry challenges and drive cutting-edge advancements in the field of data science and AI. Key Achievements: • Created smart algorithms to predict global economic and environmental variables with 98% accuracy through the establishment of advanced deep learning models (Dynamic Bayesian Networks), providing valuable insights for businesses and driving a remarkable 30% improvement in overall global economic performance. • Formulated predictive analytics solutions for analyzing technology adoption trends using a highly effective machine learning model (regime-switching regression models), enabling businesses to make data-driven decisions and maintain a competitive edge in their industries. • Devised data-driven solutions to optimize payment for ecosystem services programs by implementing a powerful machine learning model (Bayesian Neural Network), resulting in substantial cost savings of approximately $10 million. • Guided and mentored students using innovative teaching methodologies and personalized learning strategies, facilitating strong academic growth, successful conference presentations in data science and economics, including the Canadian Economics Association. • Demonstrated exceptional teaching abilities through dynamic and engaging classroom sessions, fostering a two to five-point improvement in students' scores for mathematics and computer science courses in machine learning and data science. • Achieved a 5% increase in mathematics and computer science program enrollments by promoting innovative courses on machine learning and data science, sparking students' interest, and addressing the growing demand for expertise in cutting-edge technologies in the digital age. Show less



United Nations University

• Japan
• Think Tanks
• 100 - 200 Employee

• Associate Research Fellow – Green Economics and Statistics

  • 2017 - 2019

  Led high-performance research teams, generating innovative data-driven analytical products, research reports, and briefing notes. Mentored policymakers and researchers on cutting-edge machine learning and quantitative research methods, elevating their skills in the field. Key Achievements: • Developed machine learning-powered solutions achieving 85% accuracy in predicting climate change impact on land use, crop production, and labour productivity using bio-economic and quantile regression models, resulting in improved agricultural planning and a 20% increase in the adoption rate of green infrastructure. • Created data-driven solutions with over 80% accuracy to predict the in-situ price and market value of fourteen non-renewable natural resources using the Hotelling model of exploitation, generating valuable insights for informed decision-making and resource allocation. • Designed AI-driven solutions to predict firms’ capabilities (high, medium, low, no) to introduce eco-innovations by developing and training ordered probit models, resulting in a $5M cost-saving and a 10% increase in outputs through the government’s green business support programs. • Engineered predictive analytics solutions to forecast labour productivity in agriculture and responses to green infrastructure, utilizing quantile regression models, leading to improved awareness and integration of green infrastructure into the national land-use agenda, enhancing the growth potential of farmers by 0.42 to 41.49 units. • Accomplished precise modelling of business issues, leading policy-oriented research on inclusive green growth, and supervising diverse expert teams to foster impactful policy dialogues and knowledge-sharing on social inclusion, green growth, trade, and investments. Show less

• Senior Research Fellow – Green Economics and Statistics

  • 2013 - 2016

  Led high-performance research teams, driving innovation in data-driven analytical products and knowledge materials. Mentored policymakers and researchers, equipping them with state-of-the-art quantitative research methods. Represented the institute at conferences, workshops, and meetings, facilitating impactful discussions and influencing policy decisions. Key Achievements: • Accomplished 95% accuracy in predicting the impact of intra-regional trade on food availability under global climate change and socio-economic scenarios, using machine learning-powered solutions. This achievement resulted in a remarkable 20% improvement in policy effectiveness and decision-making, advancing sustainable development agendas. • Formulated data-driven solutions employing supervised machine learning models to predict the acceptability, sustainability, and viability of water treatment innovations. This initiative led to a substantial eco-innovation market share growth of 10% in Ghana, promoting environmentally sustainable practices. • Built predictive analytics solutions based on machine learning frameworks to forecast the effects of renewable energy on employment. This endeavor resulted in the creation of 584 new jobs and a significant increase of $32M in output through geothermal power generation, fostering inclusive economic growth. • Led over 40 policy-oriented research projects focused on inclusive green growth, effectively managing diverse international teams. These initiatives facilitated data-driven policy dialogues and resulted in a 15% increase in evidence-based policy recommendations, contributing to sustainable development and economic inclusivity. • Successfully developed 20+ knowledge products on social inclusion, green growth, trade, and investments, establishing a robust network of 30+ experts and partners. Representing the institute at 15+ national and international meetings, I played a key role in driving impactful discussions and influencing policy decisions. Show less



United Nations

• United States
• International Affairs

• Research Fellow - Economics and Statistics

  • 2011 - 2013

  As a Data Scientist and Economist, I utilized cutting-edge ML algorithms and advanced statistical techniques to develop groundbreaking data-driven products and research reports in green economics. My active engagement in conferences influenced policy decisions on social inclusion, green growth, and trade.Key Achievements:• Crafted artificial intelligence-driven solutions (stochastic frontier models) that achieved 90% accuracy in predicting various economic and environmental outcomes. The implementation led to a 15% increase in data-driven strategies and 25% improvement in resource allocation efficiency.• Leveraged AI and ML algorithms to analyze diverse environmental data, resulting in a 25% increase in resource utilization efficiency and identifying 15% more eco-friendly initiatives for implementation. • Applied advanced statistical techniques and econometric models to analyze project data, resulting in a 20% improvement in project performance metrics and 30% increase in project impact on the target population. Evidence-based decision-making led to a 40% reduction in project risks.• Supported evidence-based decision-making by overseeing business issue modeling using mathematical and statistical methods, resulting in a 20% increase in accurate identification of causes and impacts of green growth policies.• Led policy-oriented research projects on inclusive green growth, policy initiatives, and program development, using advanced statistical methods and econometric models, resulting in 15 evidence-based policy recommendations, informed program design, and impactful policy dialogues.• Fostered collaboration and knowledge-sharing among diverse expert teams through effective communication and regular brainstorming, leading to data-driven knowledge products on social inclusion, green growth, trade, and investments. Established strategic partnerships, driving innovation and impactful policy initiatives. Show less

• Visiting Scholar - Statistics

  • Jan 2011 - Jun 2011

  As a Data Scientist and Economist, I leveraged state-of-the-art ML algorithms and advanced statistical methods to create innovative data-driven products and research reports in the field of statistics. My active participation in conferences played a pivotal role in shaping policy decisions related to statistical development.Key achievements:• Oversaw a team of statisticians to build an integrated database for international commodity statistics, cutting data processing time by 30% and enhancing accuracy by 25%, enabling confident data-driven decisions for commodity firms. • Prepared AI-driven analytical reports using SQL with Python and VBA, improving risk assessment accuracy by 15% and identifying new opportunities by 20%, empowering stakeholders with actionable insights for better strategic decisions.• Implemented AI solutions to forecast economic growth and public/private investments in Ivory Coast using 4-vector error correction models. Achieved 98% accuracy in predicting outcomes, optimizing budget allocation, and boosting investments in buildings and public works, fostering economic growth and development. Show less