Hire remote Machine Learning engineers near San Antonio or in a similar time zone
Charles Cook, Ph.D.
Charles has a Ph.D. in aerospace engineering and spent three years developing custom data processing and analysis programs for NASA. He specializes in scalable, enterprise-level application development and engineering solutions for exceptionally high throughputs. He is also the founder and owner of GreatVocab.com, for which he developed the core system using novel concepts in data analysis and control theory.
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Pedro Henrique Rocha Moy
Pedro is a business-oriented seasoned data scientist and data engineer with experience building and deploying production distributed data pipelines and machine learning models at scale, covering the entirety of the data lifecycle from design, construction, optimization, deployment, and monitoring of data architectures and machine learning models. Pedro's focus is to deliver solutions that are robust to changes in environment and data and flexible to address changes in business requirements.
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Saikat Banerjee
Saikat is a computational genomics scientist at the New York Genome Center. Previously, he was a postdoc at UChicago and MPI, Germany. He did a PhD in computational biophysics and a master's degree in chemistry. He is an expert in Bayesian methods, machine learning, biostatistics, and statistical genetics. During his PhD, Saikat co-founded a marketing management company. He enjoys solving problems and creating value, often learning new skills at a professional level.
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Igor Stankevich
Igor is a results-driven quantitative development professional with progressive industry experience in commodities, deep learning, computer vision, and data science. He has demonstrated hands-on financial and AI software development experience with in-depth knowledge of Python. Igor consistently attempts to find the best value-add opportunities and contribute to the team as a whole.
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Leopoldo Corona
Leopoldo is a Certified AWS Machine Learning (ML) specialist who has worked in all data-related positions. He started his career early as a data research analyst and then became a data scientist, developing risk and fraud assessing models. When Leopoldo began struggling with bringing those models to production, he transitioned to an ML position focusing more on data-centric engineering, thus becoming a data engineer. Currently, Leopoldo is the head of data engineering at Clara startup.
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Maxuel Reis
Maxuel is a data scientist and engineer with proven end-to-end data solution experience who quickly adapts to new technologies. He is skilled in batch and real-time machine learning, cloud computing (AWS, GCP, and Azure), big data (Hive and Spark), and data streams. He expertly combines data science and engineering for effective data management and business-aligned strategies. With an acting background, Maxuel has unique communication abilities that enhance teamwork and management.
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Diego Kiedanski
Diego is a Computer Engineer specializing in internet measurements and data analytics for internet traffic patterns. He has worked as a machine learning consultant on projects ranging from price optimization for insurance companies to remote sensing and computer vision to detect schools in remote areas for UNICEF. Diego has worked on three continents, from Yale University (USA) to national train companies (Luxembourg) and South America.
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Joseph Miano
Joseph is a data scientist with 3+ years of experience in computer vision, NLP, and tabular datasets. He's worked on analytics for large-scale medication adherence outreach programs, multi-task neural networks for brain microscopy image segmentation, and NLP models to detect COVID-19 outbreaks from news articles. He's also familiar with model explainability for credit risk assessment and fraud detection models. Joseph holds an MS in Computer Science with a specialization in machine learning.
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Dandan Zheng
Dandan is a senior data analyst and data scientist with 5+ years of professional experience and an extensive background in predictive models, AB testing, dashboard, and end-to-end analytics projects. She has worked in the technology, live streaming, social media platform, and oil and gas energy industries, constantly collaborating with cross-functional teams. Besides work, Dandan enjoys traveling and is a big-time computer gamer.
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Jeremy Jacobson
Jeremy is a versatile data scientist with six years of experience that includes leading machine learning research projects and managing department teams. He has built data science and ML solutions used by faculty and external partners such as CareerBuilder and UPS. He was recognized by Google Education as a Google Cloud Faculty Expert and selected to the AWS Academy Cloud Council Faculty. Adept at picking up new skills quickly, Jeremy is committed to freelancing excellence.
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Nathan Faber
Nathan is a problem solver at heart, having worked as a chemical engineer, financial data scientist, and portfolio manager. He loves to dive into messy data sets to uncover patterns and leverage the data to benefit the business. His quantitative and qualitative analysis skills in machine learning, visualization, and model creation, paired with his attention to detail and development experience in various programming languages, make him an ideal candidate for tackling any project.
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