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    Daniel Feldman

    Data Engineer at Pendo Systems, Adjunct Lecturer of Astrophysics at CUNY College of Staten Island

    Professional Background

    Daniel Feldman is an accomplished data scientist and data engineer with over 11 years of experience specializing in leveraging Python for data storytelling and analysis. His journey began in the realm of astronomy and astrophysics, where he made significant contributions through various research projects, utilizing advanced datasets from renowned telescopes including the Hubble Space Telescope. His analytical skills have enabled him to study distant galaxies, Mass atmosphere of Mars, and young stellar objects poised to evolve into planetary systems. This rich background in scientific research laid a solid foundation for his career in technology, where he has excelled at translating complex datasets into actionable insights for clients across various industries.

    In addition to his technical prowess, Daniel has held positions at various esteemed organizations. As a former Data Engineer at Pendo Systems, he honed his skills in data analysis and engineering processes to help clients harness their dark data effectively. His role as a Contract Data Scientist at Springboard allowed him to work remotely, providing him with diverse experiences and flexibility in managing data-driven projects. Furthermore, Daniel is passionate about sharing his knowledge and fostering growth in others, evident from his time as an Adjunct Lecturer at the City University of New York-College of Staten Island.

    Education and Achievements

    Daniel's academic achievements speak volumes about his dedication and intellect. He earned a Master of Arts (M.A.) in Astronomy from Boston University, achieving a commendable GPA of 3.74. Complementing this, he holds not one but two Bachelor of Science (BS) degrees in Physics from the City University of New York-College of Staten Island and Macaulay Honors College, where he achieved an impressive 3.97 GPA. This excellence in academics reflects his strong analytical and quantitative skills necessary for success in both research and technology.

    Beyond academics, Daniel has engaged in numerous organizations and initiatives aimed at enriching the community and mentoring aspiring scientists. As a Data Management Volunteer at the Boston Area Rape Crisis Center, he contributed to important social causes while enhancing his understanding of data management and its impact on vulnerable populations. His involvement in research initiatives as a Graduate Research Assistant at Boston University further solidified his expertise in applying theoretical knowledge to practical challenges in the field of astronomy.

    Notable Contributions

    Daniel's professional journey has been marked by several notable contributions that display his commitment to discovery and innovation. As part of his research endeavors, he participated in the National Science Foundation's Research Experience for Undergraduates (REU) at Northern Arizona University, where he conducted valuable research that contributes to the broader understanding of astrophysics and its applications.

    During his tenure as an Undergraduate Research Assistant at the American Museum of Natural History, Daniel collaborated with a team of researchers to explore various facets of physics and its relationship with astronomical phenomena. His experiences in these roles have not only deepened his knowledge but also sharpened his ability to convey intricate scientific ideas to a broader audience.

    Skills and Expertise

    Daniel's technical skills encompass a broad range of competencies essential for success in data-centric roles. Proficient in Python, he seamlessly weaves together statistics, Bayesian analysis, and data visualization techniques to uncover insights hidden within complex datasets. His expertise in SQL and UNIX further enhances his ability to manipulate and analyze vast quantities of data, making him an invaluable asset for organizations seeking to optimize their data processes.

    Invitation

    Currently, Daniel is seeking a new opportunity where he can continue his passion for uncovering stories from data and communicating insightful findings to technical and non-technical audiences alike. If you are in search of a dedicated, detail-oriented data expert to help illuminate the hidden narratives within your datasets, or if you are intrigued by the prospect of discussing the wonders of astronomy and its implications on our understanding of the universe, Daniel encourages you to reach out via email. His unique background and blended experiences in both the scientific and technological fields equip him with a distinctive perspective that can greatly benefit any organization looking to unlock the potential of their data.

    Related Questions

    How did Daniel Feldman transition from a background in astronomy to a career in data science?
    What specific projects has Daniel Feldman worked on that showcase his expertise in using Python for data analysis?
    In what ways has Daniel's experience as an Adjunct Lecturer influenced his approach to data communication and storytelling?
    What are the most significant contributions Daniel Feldman has made during his time at the National Science Foundation’s Research Experience for Undergraduates (REU)?
    How can organizations benefit from the skills and knowledge that Daniel Feldman brings as a data expert?
    Daniel Feldman
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    Location

    Greater New York City Area