
Fikrewold Bitew
Scientific
Services offered
As a dynamic and forward-thinking Sr. data scientist and demographer, I spearhead the conversion of data into actionable insights that power business operations, mitigate organizational risks, secure funding, and unveil consumer behaviors. My expertise encompasses a wide range of areas within machine learning/AI and deep learning, including Neural Networks, Natural Language Processing (NLP), computer vision, big data analytics (utilizing Hive in Hadoop, Spark, and Snowflake), statistical modeling, data mining/analysis, and quantitative research. With a proven record of publishing 14 articles in reputable peer-reviewed journals, I am dedicated to advancing the field of data science. Proficient in various programming languages and tools, such as Python, R, SQL, and Apache Spark, alongside statistical software like STATA, SAS, and SPSS, I am deeply committed to harnessing data and technology for social good.
My academic background features a PhD in Applied Demography from UTSA, a Master's Degree in Artificial Intelligence and Machine Learning from The University of Texas at Austin, and Bachelor's and Master's Degrees in Applied Mathematics and Statistics from Addis Ababa University. I have made substantial contributions to the field, evidenced by 14 peer-reviewed journal articles published in esteemed ML journals like Genus, Spatial Demography, and Public Health Nutrition. Additionally, I have provided consultancy services for UNICEF, contributing to projects focused on social and behavior change, as well as nutrition.
Experience
Dr. Fikrewold H. Bitew is a seasoned Senior Research Data Scientist with extensive expertise in machine learning, AI, data science, and institutional research. With a robust background in applied demography, statistics, and data analytics, he has consistently delivered impactful solutions in academia, international organizations, and public health sectors.
He excels in developing predictive models, conducting statistical analyses, and leveraging big data technologies to address complex challenges. His work spans diverse domains, including student retention modeling, public health analytics, and global nutrition data analysis, with significant contributions to organizations like UNICEF, CDC Ethiopia, and The University of Texas at San Antonio (UTSA).
Key Strengths & Skills
- Technical Expertise: Advanced proficiency in machine learning, natural language processing (NLP), and deep learning frameworks (PyTorch, TensorFlow). Skilled in Python, R, and SQL, with experience in big data tools like Hive, Hadoop, and PySpark.
- Quantitative Research: Extensive experience in statistical modeling, spatial analysis, and data visualization using tools like STATA, SPSS, ArcGIS/QGIS.
- Cloud Technologies: Proficient in AWS, Azure, and other cloud platforms, with expertise in deploying cloud-based solutions.
- Leadership & Collaboration: Proven ability to manage cross-functional teams, foster collaboration across global stakeholders, and deliver data-driven insights in diverse, multicultural environments.
Key Achievements
- Developed and deployed machine learning models to predict student enrollment patterns and retention rates at UTSA.
- Led technical support and data dissemination for the UNICEF-WHO-The World Bank Joint Child Malnutrition Estimates, advancing global health initiatives.
- Streamlined institutional data reporting processes, saving time and enhancing decision-making capabilities for university leadership.
- Published 14 peer-reviewed articles, contributing to knowledge advancement in applied demography and data science.
Education
Dr. Fikrewold H. Bitew possesses a strong academic foundation with advanced degrees emphasizing data science, artificial intelligence, and applied demography. His education integrates technical expertise in machine learning and AI applications with profound knowledge of demographic research and statistical methodologies to address real-world challenges.
Ph.D. in Applied Demography/Statistics
The University of Texas at San Antonio
Focus: Statistical modeling, population studies, and quantitative research. Developed advanced analytical techniques and predictive modeling strategies.
Master’s in Artificial Intelligence & Machine Learning: Business Applications
The University of Texas at Austin
Focus: Applied machine learning, deep learning, natural language processing, and AI-driven business solutions.
Master’s in Demography and Population Studies
Addis Ababa University
Focus: Population dynamics, public health analytics, and statistical research with applications in global health and development.
Bachelor’s in Applied Mathematics and Statistics
Addis Ababa University
This education equips him with a unique blend of analytical rigor, AI expertise, and demographic insight, making him highly adept at addressing challenges in data-driven decision-making and global development.
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