Candidate Information Name Available: Register for Free Title Machine Learning Engineer Target Location US-TX-Lewisville Email Available with paid plan Phone Available with paid plan	20,000+ Fresh Resumes Monthly     View Phone Numbers     Receive Resume E-mail Alerts     Post Jobs Free     Link your Free Jobs Page     ... and much more Register on Jobvertise Free
Search 2 million Resumes Keywords: City or Zip:	Related Resumes

Candidate's Name
Lewisville, TX Street Address
EMAIL AVAILABLE / PHONE NUMBER AVAILABLEGitHub LinkedInEDUCATIONPh.D. in Computer Science August Street Address   December 2023University of Missouri - Columbia, MOMaster of Science in Information Engineering September 2013  December 2014Robert Gordon University - Aberdeen, UKBachelor of Technology in Computer Science October 2005  October 2010Federal University of Technology Akure - Ondo, NGEXPERIENCESenior AI /Machine Learning EngineerJPMorgan Chase - Plano, TX October 2023 - CurrentDevelop Artificial Intelligence and Machine Learning (AI/ML) Credit Risk Models to support Chase Auto acquisitions, pricing, loss prevention, repossession, and recovery.Perform ongoing testing and monitoring of Chase Auto Credit Risk models.Analyze potential macroeconomic impacts on the Credit Risk models and create mitigation strategies/overlays.Research new explainability and validation techniques for AI/ML models.Document and present model developments to Model Governance, Risk Policy, and Senior LeadershipInformatics Engineering InternGenentech - San Francisco, CA May 2023  September 2023Contributed to developing a Graph-Based Neural network that predicts compounds that have the potential to be combined synergistically in drug design.Carried out extensive data analysis on the Human Liver Microsome 'in vitro' data to connect the intrinsic variability of the prospective performance of custom 'in silico' models and understand the uncertainty estimates provided by the Graph Neural Network ensembles.Graduate Research AssistantUniversity of Missouri - Columbia, MO August 2018  May 2023Carried out research to designed AI / Deep Learning tools to predict ion-binding sites.Published academic articles on my research.Attended and presented my research results at conferences.Data Scientist InternJPMorgan Chase & Co - Plano, TX June 2022  August 2022Implemented explainable AI techniques to understand and address the sensitivity of certain variables to the predictive performance of the Auto Loan Model thereby minimizing losses on loans.NLP Research InternSage Bionetworks - Seattle, WA June 2021  August 2021Created NLP Machine Learning tools for the annotation of sensitive information from clinical notes using the following frameworks: BERT, NeuroNer and SparkData Scientist InternPrecise Software Solutions - Rockville, Maryland May 2020  August 2020Modeled and Implemented a Graph Database Solution with Network Analysis for the FDA Food traceability challenge..Software EngineerSeamfix Nigeria Limited - Lagos, NG December 2015  July 2018Worked on back/front end Technologies such as Core Java/J2EE, Springboot, Angular, React Native, JavaScript, JSP, HTML, CSSManaged the web-based SIM Registration and Operations Module on the KYC solutions for the biggest telco in Africa - MTN Nigeria which helped them remain compliant with Nigeria regulatory body, thus averting 5 billion USD in sanction.PUBLICATIONS1. Essien C, Jiang L, Wang D, Xu D. Prediction of Protein IonLigand Binding Sites with ELECTRA.Molecules. 202328(19):6793. https://doi.org/10.3390/molecules281967932. C. Essien, F. He, M. Hannink, M. Popescu and D. Xu, "Extraction of Gene Regulatory Relation Using BioBERT," 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Las Vegas, NV, USA, 2022, pp. 3351-3355.3. C. Essien, D. Wang and D. Xu, "Capsule Network for Predicting Zinc Binding Sites in Metalloproteins,"2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), San Diego, CA, USA, 2019, pp. 2337-2341.4. Yan, Y., Yu, T., Muenzen, K., Liu, S., Boyle, C., Koslowski, G., Zheng, J., Dobbins, N., Essien, C., Liu, H. and Omberg, L., 2022. The NLP Sandbox: an efficient model-to-data system to enable federated and unbiased evaluation of clinical NLP models. arXiv preprint arXiv:2206.14181.5. Zigo, M., Kerns, K., Sen, C. Essien. Zinc is a master-regulator of sperm function associated with binding, motility,and metabolic modulation during porcine sperm capacitation. Commun Biol 5, 538 (2022).6. L. Jiang, Y. Jiang, C. Wang, C. Essien, J. Wang, A. Ma, Q. Ma, and D. Xu, Machine learning development environment for single-cell sequencing data analyses, 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Las Vegas, NV, USA, 2022, pp. 3824-38267. Essien, C., Wang, N., Fei, Yu, Yang, Manshour, N., Dong Xu. 2024 Prediction of coordinated metal ion- ligand binding sites using geometry-aware graph neural networks [in review]TECHNICAL SKILLSPython, R, JAVA, C#, JavaScript, Neural Networks, Machine Learning, Natural Language Processing (NLP), Pytorch, Keras, TensorFlow, MongoDB, SQL, Quantitative Research, Data Engineering, Data Visualization, Github, Amazon Web Service (AWS), Azure, Google Computing Services, Docker, Pyspark