Hire remote R developers near Atlanta or in a similar time zone
Andrew Tilley
Andrew has nearly 10 years of experience deploying predictive algorithms and end-to-end data solutions, increasing his companies' net revenue by tens of millions of dollars. His technical acumen, combined with deep communication skills to both technical and non-technical colleagues, ensures he has a broad impact across teams who work with him. Whether the end result is a data product or a detailed analysis, Andrew relishes the opportunity to solve business problems with machine learning.
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Juan José Leitón Montero
Juan is a data scientist and developer with ten years of industry experience and a master's degree in statistics. During his career, Juan has been focusing on renewable energy, climate projections, and creating academic courses. Juan believes in continuous education and is working toward a master's degree in applied mathematics at the University of Costa Rica, where he teaches statistics and engineering to graduate students.
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Robert Pehlman
Robert is a seasoned data scientist and has worked for Mastercard, United Healthcare, and currently, Google, where he supports the Google News app. He was also a PhD student in statistics at North Carolina State University while researching causal inference, reinforcement learning, and functional data analysis. Robert's passion is solving challenging data problems by building scalable models and engineering new features to improve model performance.
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Matthew de Marte
Matthew is a data scientist who has worked primarily in professional baseball, an incredibly fast-paced and demanding industry. He has utilized R and SQL databases with strengths relying on machine learning and predictive modeling to provide better data-driven decisions. Matthew is a fantastic problem solver with a data science skill set that can communicate technical findings to non-technical audiences.
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Robert Tan
Robert has extensive SaaS experience; his clients span the United States, Canada, Qatar, Jamaica, UAE, and the UK. He develops interactive data applications and excels at data harvesting, cleaning, and visualization. Robert leads projects with the utmost professionalism and care. Some of his past clients include an international airport and two property management firms with a combined AUM of $54 billion.
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Jose Rolando Josue
Combining the technical knowledge of a bachelor's degree in business engineering with the analytical skills of a master's degree in data science, Jose has 7+ years of experience in marketing and product analytics, business intelligence, experiment design, user journeys, and understanding the nature of customer's decisions. He enjoys learning new skills, finding creative ways of solving business problems, and helping the community by teaching future professionals how to tell a story with data.
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Alex Risman
In Alex's current role, he uses artificial intelligence to automatically detect diseases in 2D and 3D medical images along with some algorithms to achieve superhuman performance. Previously, he worked as a data scientist at an eCommerce company, where he built and deployed a deep-learning-based product search engine.
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Juan Manuel Ortiz de Zarate
Currently, Juan is a PhD candidate at the University of Buenos Aires, researching the subjects of AI, NLP, and social networks. He has over a decade of professional development experience under his belt. For the last few years, he’s been immersing himself in various types of data science projects and loving every minute of it. Juan relishes taking on data problems, building prediction models, and learning state-of-the-art techniques.
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Patrick Keenum
Patrick is a senior full-stack engineer with more than 10 years of experience developing beautiful, reliable, and scalable products. He is passionate about bringing ideas from conception to launch, working with clients of all levels of technical acumen, and building products that help companies grow.
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Christopher Karvetski
Dr. Karvetski has ten years of experience as a data and decision scientist. He has worked across academia and industry in a variety of team and client settings, and has been recognized as an excellent communicator. He loves working with teams to conceive and deploy novel data science solutions. He has expertise with R, SQL, MATLAB, SAS, and other platforms for data science.
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Daniel Doyle
Daniel is a data scientist who builds predictive models, data visualizations, and dashboards on large datasets with expertise in the staffing and investment management fields. He made a graph neural network to predict risk on a construction site reducing errors by 60%. Daniel improved a predictive modeling framework, handling millions of records on policyholder behavior using R and H2O. His models are used in financial forecasts and dashboards to catch aberrant behavior as it unfolds.
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