Available to hire
Hi, I’m Casey Affleck, a passionate software engineer and data scientist based in Nairobi. I specialize in leveraging advanced data science techniques and programming skills to extract meaningful insights from complex datasets. I’ve worked with tools like Tableau, Kaggle, and Amazon Web Services, and I’m experienced in building innovative applications like a Calorie Tracker App using Swift.
I have a solid background in bioinformatics, having worked at The National Institutes of Health where I applied Python and bioinformatics tools to analyze genomic data. Currently, I work at L3Harris Technologies focusing on advanced data science projects and interactive dashboards. I’m driven by innovation and continuous learning, especially in AI training and data analytics, and I’m always excited to apply my skills to make an impact.
Skills
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Language
Spanish; Castilian
Advanced
Telugu
Fluent
English
Fluent
Turkish
Intermediate
Hindi
Beginner
Work Experience
Software Engineer/Data Scientist at L3Harris Technologies
July 1, 2023 - PresentApplied advanced data science techniques in R to analyze ground-to-flight communication data for the FAA. Developed interactive R Shiny dashboards for real-time visualization of critical communication metrics. Collaborated with cross-functional teams to integrate data insights into strategic decision-making processes. Conducted performance tuning and optimization on data analytics pipelines, improving processing efficiency by 30%. Presented findings and recommendations to executive stakeholders, influencing project direction and resource allocation. Mentored junior team members on data analysis techniques and best practices. Led initiatives to implement automated data validation processes, reducing manual effort by 40%. Researched and implemented new machine learning algorithms to enhance predictive analytics capabilities. Coordinated with external vendors to integrate third-party data sources into existing analytical frameworks. Received quarterly awards for outstanding contribution t
Bioinformatics Developer at The National Institutes of Health
May 31, 2022 - July 23, 2025Engineered Python programs to query NCBI databases and analyze mRNA sequences for genomic insights. Developed a scalable pipeline for processing large-scale genomic data, reducing processing time by 50%. Implemented data visualization techniques using Matplotlib and Plotly to communicate complex findings effectively. Authored technical reports and research papers summarizing findings for peer-reviewed publications. Designed and validated machine learning models for predicting genetic variations linked to disease susceptibility. Collaborated with biologists and geneticists to interpret computational results in biological contexts. Conducted regular code reviews and contributed to team-wide coding standards and best practices. Presented research findings at international conferences and symposiums, gaining recognition in the bioinformatics community. Coordinated training sessions on bioinformatics tools and techniques for new team members.
Student Intern at National Institutes of Health
July 31, 2018 - July 23, 2025Developed proficiency in Linux command line operations and scripting for data manipulation. Analyzed RNA sequencing data using Python scripts and bioinformatics tools. Contributed to the development of automated pipelines for processing and analyzing genomic data. Assisted in experimental design and data collection procedures under the guidance of senior researchers. Presented research findings to lab members and participated in scientific discussions. Gained insights into RNA regulation mechanisms and their implications in cellular biology. Documented experimental procedures and results in laboratory notebooks. Collaborated with interdisciplinary teams to integrate computational and experimental approaches.
FIRE Summer Fellowship - Capital One Machine Learning Stream at First Year Innovation and Research Experience (FIRE)
June 30, 2020 - July 23, 2025Collaborated on machine learning projects including Speech Recognition and Facial Recognition using Python. Designed and implemented a machine learning model for Skin Lesion Classification using Keras and TensorFlow. Conducted literature reviews and implemented state-of-the-art algorithms from recent publications. Optimized neural network architectures to improve model accuracy by 15%. Analyzed and preprocessed medical imaging data for training machine learning models. Documented project progress and findings in technical reports and presentations. Participated in weekly research seminars and workshops on machine learning and AI applications. Demonstrated leadership by mentoring undergraduate students in AI and machine learning techniques. Received accolades for exceptional performance and contributions to innovative research projects.
Software Engineer/Data Scientist at L3Harris Technologies
July 1, 2023 - PresentApplied advanced data science techniques in R to analyze ground-to-flight communication data for the FAA. Developed interactive R Shiny dashboards for real-time visualization of critical communication metrics. Collaborated with cross-functional teams to integrate data insights into strategic decision-making processes. Conducted performance tuning and optimization on data analytics pipelines, improving processing efficiency by 30%. Presented findings and recommendations to executive stakeholders, influencing project direction and resource allocation. Mentored junior team members on data analysis techniques and best practices. Led initiatives to implement automated data validation processes, reducing manual effort by 40%. Researched and implemented new machine learning algorithms to enhance predictive analytics capabilities. Coordinated with external vendors to integrate third-party data sources into existing analytical frameworks. Received quarterly awards for outstanding contribution t
Bioinformatics Developer at The National Institutes of Health
May 31, 2022 - July 23, 2025Engineered Python programs to query NCBI databases and analyze mRNA sequences for genomic insights. Developed a scalable pipeline for processing large-scale genomic data, reducing processing time by 50%. Implemented data visualization techniques using Matplotlib and Plotly to communicate complex findings effectively. Authored technical reports and research papers summarizing findings for peer-reviewed publications. Designed and validated machine learning models for predicting genetic variations linked to disease susceptibility. Collaborated with biologists and geneticists to interpret computational results in biological contexts. Conducted regular code reviews and contributed to team-wide coding standards and best practices. Presented research findings at international conferences and symposiums, gaining recognition in the bioinformatics community. Coordinated training sessions on bioinformatics tools and techniques for new team members.
Student Intern at National Institutes of Health
July 31, 2018 - July 23, 2025Developed proficiency in Linux command line operations and scripting for data manipulation. Analyzed RNA sequencing data using Python scripts and bioinformatics tools. Contributed to the development of automated pipelines for processing and analyzing genomic data. Assisted in experimental design and data collection procedures under the guidance of senior researchers. Presented research findings to lab members and participated in scientific discussions. Gained insights into RNA regulation mechanisms and their implications in cellular biology. Documented experimental procedures and results in laboratory notebooks. Collaborated with interdisciplinary teams to integrate computational and experimental approaches.
FIRE Summer Fellowship - Capital One Machine Learning Stream at First Year Innovation and Research Experience (FIRE)
June 30, 2020 - July 23, 2025Collaborated on machine learning projects including Speech Recognition and Facial Recognition using Python. Designed and implemented a machine learning model for Skin Lesion Classification using Keras and TensorFlow. Conducted literature reviews and implemented state-of-the-art algorithms from recent publications. Optimized neural network architectures to improve model accuracy by 15%. Analyzed and preprocessed medical imaging data for training machine learning models. Documented project progress and findings in technical reports and presentations. Participated in weekly research seminars and workshops on machine learning and AI applications. Demonstrated leadership by mentoring undergraduate students in AI and machine learning techniques. Received accolades for exceptional performance and contributions to innovative research projects.
Software Engineer/Data Scientist at L3Harris Technologies
July 1, 2023 - PresentApplied advanced data science techniques in R to analyze ground-to-flight communication data for the FAA. Developed interactive R Shiny dashboards for real-time visualization of critical communication metrics. Collaborated with cross-functional teams to integrate data insights into strategic decision-making processes. Conducted performance tuning and optimization on data analytics pipelines, improving processing efficiency by 30%. Presented findings and recommendations to executive stakeholders, influencing project direction and resource allocation. Mentored junior team members on data analysis techniques and best practices. Led initiatives to implement automated data validation processes, reducing manual effort by 40%. Researched and implemented new machine learning algorithms to enhance predictive analytics capabilities. Coordinated with external vendors to integrate third-party data sources into existing analytical frameworks. Received quarterly awards for outstanding contribution t
Bioinformatics Developer at The National Institutes of Health
May 31, 2022 - July 23, 2025Engineered Python programs to query NCBI databases and analyze mRNA sequences for genomic insights. Developed a scalable pipeline for processing large-scale genomic data, reducing processing time by 50%. Implemented data visualization techniques using Matplotlib and Plotly to communicate complex findings effectively. Authored technical reports and research papers summarizing findings for peer-reviewed publications. Designed and validated machine learning models for predicting genetic variations linked to disease susceptibility. Collaborated with biologists and geneticists to interpret computational results in biological contexts. Conducted regular code reviews and contributed to team-wide coding standards and best practices. Presented research findings at international conferences and symposiums, gaining recognition in the bioinformatics community. Coordinated training sessions on bioinformatics tools and techniques for new team members.
Student Intern at National Institutes of Health
July 31, 2018 - July 23, 2025Developed proficiency in Linux command line operations and scripting for data manipulation. Analyzed RNA sequencing data using Python scripts and bioinformatics tools. Contributed to the development of automated pipelines for processing and analyzing genomic data. Assisted in experimental design and data collection procedures under the guidance of senior researchers. Presented research findings to lab members and participated in scientific discussions. Gained insights into RNA regulation mechanisms and their implications in cellular biology. Documented experimental procedures and results in laboratory notebooks. Collaborated with interdisciplinary teams to integrate computational and experimental approaches.
FIRE Summer Fellowship - Capital One Machine Learning Stream / First Year Innovation and Research Experience (FIRE) at Maryland
June 30, 2020 - July 23, 2025Collaborated on machine learning projects including Speech Recognition and Facial Recognition using Python. Designed and implemented a machine learning model for Skin Lesion Classification using Keras and TensorFlow. Conducted literature reviews and implemented state-of-the-art algorithms from recent publications. Optimized neural network architectures to improve model accuracy by 15%. Analyzed and preprocessed medical imaging data for training machine learning models. Documented project progress and findings in technical reports and presentations. Participated in weekly research seminars and workshops on machine learning and AI applications. Demonstrated leadership by mentoring undergraduate students in AI and machine learning techniques. Received accolades for exceptional performance and contributions to innovative research projects.
Software Engineer/Data Scientist at L3Harris Technologies
July 1, 2023 - PresentApplied advanced data science techniques in R to analyze ground-to-flight communication data for the FAA. Developed interactive R Shiny dashboards for real-time visualization of critical communication metrics. Collaborated with cross-functional teams to integrate data insights into strategic decision-making processes. Conducted performance tuning and optimization on data analytics pipelines, improving processing efficiency by 30%. Presented findings and recommendations to executive stakeholders, influencing project direction and resource allocation. Mentored junior team members on data analysis techniques and best practices. Led initiatives to implement automated data validation processes, reducing manual effort by 40%. Researched and implemented new machine learning algorithms to enhance predictive analytics capabilities. Coordinated with external vendors to integrate third-party data sources into existing analytical frameworks. Received quarterly awards for outstanding contribution t
Bioinformatics Developer at The National Institutes of Health
May 31, 2022 - July 23, 2025Engineered Python programs to query NCBI databases and analyze mRNA sequences for genomic insights. Developed a scalable pipeline for processing large-scale genomic data, reducing processing time by 50%. Implemented data visualization techniques using Matplotlib and Plotly to communicate complex findings effectively. Authored technical reports and research papers summarizing findings for peer-reviewed publications. Designed and validated machine learning models for predicting genetic variations linked to disease susceptibility. Collaborated with biologists and geneticists to interpret computational results in biological contexts. Conducted regular code reviews and contributed to team-wide coding standards and best practices. Presented research findings at international conferences and symposiums, gaining recognition in the bioinformatics community. Coordinated training sessions on bioinformatics tools and techniques for new team members.
Student Intern at National Institutes of Health
July 31, 2018 - July 23, 2025Developed proficiency in Linux command line operations and scripting for data manipulation. Analyzed RNA sequencing data using Python scripts and bioinformatics tools. Contributed to the development of automated pipelines for processing and analyzing genomic data. Assisted in experimental design and data collection procedures under the guidance of senior researchers. Presented research findings to lab members and participated in scientific discussions. Gained insights into RNA regulation mechanisms and their implications in cellular biology. Documented experimental procedures and results in laboratory notebooks. Collaborated with interdisciplinary teams to integrate computational and experimental approaches.
FIRE Summer Fellowship - Capital One Machine Learning Stream at First Year Innovation and Research Experience (FIRE)
June 30, 2020 - July 23, 2025Collaborated on machine learning projects including Speech Recognition and Facial Recognition using Python. Designed and implemented a machine learning model for Skin Lesion Classification using Keras and TensorFlow. Conducted literature reviews and implemented state-of-the-art algorithms from recent publications. Optimized neural network architectures to improve model accuracy by 15%. Analyzed and preprocessed medical imaging data for training machine learning models. Documented project progress and findings in technical reports and presentations. Participated in weekly research seminars and workshops on machine learning and AI applications. Demonstrated leadership by mentoring undergraduate students in AI and machine learning techniques. Received accolades for exceptional performance and contributions to innovative research projects.
Education
Ph.D. at University of Maryland
January 1, 2024 - December 31, 2024Bachelor's degree at University of Maryland
May 1, 2022 - May 31, 2022High School Diploma at Mount Hebron High School
January 1, 2019 - December 31, 2019Ph.D. at University of Maryland
January 1, 2024 - December 31, 2024Bachelor's degree at University of Maryland
May 1, 2022 - May 1, 2022High School Diploma at Mount Hebron High School
January 1, 2019 - January 1, 2019Ph.D. at University of Maryland
January 1, 2024 - December 31, 2024Bachelor's degree at University of Maryland
January 1, 2022 - May 31, 2022High School Diploma at Mount Hebron High School
January 1, 2019 - January 31, 2019Ph.D. at University of Maryland
January 1, 2024 - January 1, 2024Bachelor's degree at University of Maryland
May 1, 2022 - May 31, 2022High School Diploma at Mount Hebron High School
January 1, 2019 - January 1, 2019Qualifications
Industry Experience
Government, Life Sciences, Healthcare, Software & Internet, Professional Services, Financial Services
Skills
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
Intermediate
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