Hire Freelance XGBoost Developers and Engineers
Tory Borsboom-Hanson
Tory is a data scientist and forecasting specialist with extensive experience in experimental design, AB testing, and leadership roles. His stack of choice includes Python, SQL, Pandas, PySpark, Hadoop, MLFlow, XGBoost, and Scitkit-learn. Beyond data science and model development, he is an expert at data visualization and reporting, especially to non-technical audiences. He often remarks that "a poorly presented analysis can often be worse than no analysis at all."
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Samuel López Santamaría
Samuel is a seasoned data scientist experienced in building intelligent systems. He worked on solutions to predict aircraft delays for Lufthansa and upcoming graffiti on trains for Deutsche Bahn. He has also led an Agile team researching applications of reinforcement learning for autonomous vehicles. Samuel has deep expertise working with Python and has engaged in all stages of the data science pipeline, from data engineering to model training and deployment to the cloud (Azure, GCP).
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Alex Eftimiades
Alex is an experienced data scientist, statistician, and Python engineer. He has built models that identify financial crime and classify text communications using tools ranging from XGBoost to cutting-edge research and deployed them on AWS Lambda from Docker containers. He authored the now open source Model Validation Toolkit, used at FINRA to perform statistically rigorous model validation and monitoring.
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Joslyn Lim
Joslyn is a seasoned data practitioner with demonstrated experience across multiple industries, including technology consulting and customer service. With her academic background in applied statistics and a skillset in machine learning, data analytics, Python, and SQL, Joslyn has delivered numerous projects with positive business impacts on customers.
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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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Aurélien Mazoyer
Aurélien is a senior software engineer who has implemented large-scale systems for big technology companies, such as Tomtom, Amadeus, and Blablacar. As a search engine specialist, he has designed tailor-made solutions leveraging open-source search technologies. At Blablacar, he created a production-ready pricing service leveraging a machine learning model (XGBoost) to predict prices, set up CI/CD with regression testing for service rollout, and developed new features with data scientists.
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Carina van der Zee
A seasoned AI/ML and statistics expert, Carina leverages her comprehensive skill set to deliver impactful solutions as a consultant, freelance, and CTO. Her impressive trajectory spans from top Wall Street banks to technical leadership in the tech sector, backed by robust academic credentials in mathematics, engineering, and business. Passionate about solving analytics, automation, and optimization challenges, Carina propels businesses into the future with her data-driven approach.
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Felice Rando
Felice is an expert in machine learning, predictive analytics, and big data, having built dozens of solutions across multiple verticals, including finance, fraud, telecommunications, and pharmaceutical research, deriving business value from raw data. He has served both as a practitioner and analytics executive in organizations such as OECD, the University of Washington, First Data, ID Analytics, and multiple start-ups. Felice has a Master's degrees in theoretical and applied statistics.
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Matthew Alhonte
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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Andrew Burnie
Andrew is an expert in extracting commercially valuable insights from data, with a specialty in text analysis. He has experience in the retail, insurance, and other financial sectors. Andrew earned a PhD in social media analysis, funded by the UK's national institute for data science and AI, and a master's degree in management and economics from the University of Cambridge. He enjoys using machine learning and statistics to help companies get the most out of their data.
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Brian Todd
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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