Hire remote data scientists near Orlando or in a similar time zone
John Muchovej
Freelance Data Scientist
John is a recent computer and cognitive science graduate. He primarily works in deep learning, previously focusing on CV and NLP but now focuses on RL and uses ML to interrogate the brain. He's currently a researcher at MIT and Harvard and has been working as an AI engineer for two years—both on self-started projects as well as freelance. He also spends some of his weekends teaching to undergraduate and high school students.
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Paul W Evans
Freelance Data Scientist
Paul has spent all ten years of his career in data. Data automation, process, warehousing, analytics, and business intelligence are just some of the many roles Paul has filled to help companies improve and even get to the cutting edge. Want to reduce your reliance on Excel? Paul is your guy. Most jobs he has held have been very outward customer-facing, so he's always looking out for clients' best interests and is conscientious of their needs.
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Edward Kench
Freelance Data Scientist
Edward is a big data/senior cloud architect and a longtime leader of successful large and risky data project deliveries via Agile methods. Currently, he's working with Fortune 500 companies on major transformation initiatives and digital modernization, i.e. cloud strategies. He specializes in Azure Data Factory, SQL, data lakes, Azure Databricks, Spark, Blob Storage, Azure Data Warehouse CosmosDB, logic apps, Azure Functions, Power BI, & Tableau.
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Jonathan Rhone
Freelance Data Scientist
Jonathan is a full-stack engineer who's as comfortable working on large-scale distributed systems as he is on client-facing single-page web apps. Jon also excels at working with big data, and has frequently worked on a petabyte scale.
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Abraham Bruck
Freelance Data Scientist
Abraham's been working with databases since 1984, including Oracle, PostgreSQL, MS Access, MySQL, and more in Unix, Windows, and AWS (cloud) environments. His work experience runs the gamut from data analysis, modeling, migration, conversion, integration, aggregation, mining, optimization, performance tuning, warehousing to extensive, varied, and detailed reporting.
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Lawrence Zhou
Freelance Data Scientist
Lawrence is a software developer and quantitative analyst with over 12 years of experience in software development and quantitative modeling. He's worked at Citigroup, Traxis Partners, as well as co-founding a Y-Combinator funded startup. Lawrence prefers projects that use both his financial and programming backgrounds, but he also enjoys working with and analyzing data—either in analysis, visualization, or machine learning.
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Matthew Alhonte
Freelance Data Scientist
Matt has officially worked as a Python-based data scientist for the past six years; however, he's spent the last ten at the intersection of stats and programming (before the term data scientist had caught on). He combines strong technical skills with a rigorous background in experiment design and statistical inference. More recently, he's been focusing on machine learning, including some natural language processing and computer vision.
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Brian Todd
Freelance Data Scientist
Brian is an experienced data scientist and machine learning engineer with a track record of researching and deploying a wide range of models for natural language processing (NLP) tasks, computer vision algorithms, classical machine learning algorithms, Bayesian statistical models, time series analysis models, and large-scale data mining algorithms.
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Vimal Vachhani
Freelance Data Scientist
Vimal is a senior enterprise data architect with an extensive background in database and business intelligence fundamentals. He has over 14 years of experience across industries as a user experience architect, data modeler, data architect, solutions developer, and business analyst. Vimal brings in-depth knowledge to projects with BI tools, including SQL Server, analysis, integration and reporting services, as well as big data fundamentals.
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Keyvis Damptey
Freelance Data Scientist
Keyvis uses statistics and mathematics to discover valuable information by identifying, testing, and verifying relationships between all the factors influencing your business. This process unveils the nuances to the "lay of the land" when it comes to the costs, operations, or customer sentiment that your organization must work with. From there, you both can discover the impact of actions and design strategies around your organization's goals.
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