Hire data analysts near London or in a similar time zone
Maximilian Hopf
Max is a data science and machine learning expert specializing in deep learning and natural language processing. He is an expert in the finance and healthcare domains. He helped build one of Germany's most highly funded fintechs and successfully founded his own AI company in London. Max also built and led the data team of Garner Health for one of the most successful US healthtech companies, scaling the team from one to 25 people and more than $100 million in annual revenue.
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Colan Walsh
Colan is an experienced senior financial quantitative developer and researcher with experience across various asset classes and trading venues. He has a multidisciplinary background, working in quant development, quant research, and options trading for multiple investment banks and hedge funds.
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Anna Tshngryan
Anna is a data scientist with four years of experience in data analysis and machine learning. She works on end-to-end processes, from data scraping, data collection, and pre-processing, cleaning, and data visualization to predictive modeling development. She is skilled in training a number of ML models, comparing them, and conducting error analyses. Anna is looking for projects that allow her to use data and machine learning to solve complex problems.
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Brendan Walsh, PhD
Dr. Brendan has over ten years of experience in digital transformation and bespoke development projects. His experience at Accenture and Wood Group allowed him to work for some of the largest companies in the UK and Ireland across the telecommunications, energy, and retail sectors. As a freelancer, Dr. Brendan specializes in systems development, including business intelligence, data engineering, Azure iPaaS (Integration Platform as a Service), and Microsoft Dynamics 365 Business Central.
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Daniel Coderre
Daniel is an experienced data professional with a decade of experience in building analytical systems. He is happiest working on the full stack, from engineering storage systems and processing pipelines to data analysis, presentation, and building front-end dashboards. For the past several years, Daniel has been heavily into machine learning (ML) and has applied it to create value from real-world data. He has a PhD in experimental physics, so ML is not the only tool in his toolbox.
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Henrik Sergoyan
Henrik is a data scientist with over eight years of experience specializing in natural language processing, focusing on GenAI and retrieval-augmented generation (RAG) solutions. He excels in building end-to-end data solutions, including data collection, processing, analytics, reporting, and deployment. Proficient in SQL and NoSQL databases, Henrik combines strong project management skills with innovative problem-solving to deliver exceptional results.
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Nicolas Keller
With a strong mathematical background (a master's degree in mathematics), Nicolas is a passionate data scientist who can contribute the ideal combination of machine learning knowledge, practical programming skills, and a problem solving and analytical mindset to a project. He has a demonstrated history of transforming business problems into data-driven solutions and recently has worked as a data scientist at the global insurance company, Allianz.
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Mohamed Ahmed
Mohamed is a big data platform architect with 15 years of experience in the IT industry. He excels with distributed systems, data engineering, machine learning, and DevOps. Mohamed builds robust batch and real-time data platforms for stakeholders and moves companies to state-of-the-art data platforms. He designed GDPR-compliant data lakes and optimized an ETL pipeline, which saved the client hundreds of thousands of dollars annually. Mohamed is pragmatic and has an agile mindset.
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Michał Porębski
Michał is an experienced ETL, data warehousing, reporting, and data visualization specialist with an academic background in statistics. His past projects include design and implementation of entire reporting and data warehousing setups, design and creation of reports and dashboards, data pipelines, and query optimizations. He has experience in all stages of data management—extraction, transformation, and analysis.
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Giovanni Biondaro
Giovanni is passionate about data analysis with Python and machine learning. As a data scientist in one of the leading Dutch banks, he developed banking and credit risk models. Giovanni has built models to predict client behavior during a crisis, defined business strategies, attended investor meetings, and measured the validity of credit risk models used in banking, such as AIRB and IFRS9. Giovanni develops trading bots on cryptocurrency and sports betting markets in his free time.
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Javier Saez Gallego
Javier is a passionate data scientist who builds data-driven software products and helps organizations transform numbers into optimal decisions. With a multidisciplinary background, he has analyzed highly dimensional datasets and built machine learning models—starting from the research stage to the implementation phase. Javier is careful, very organized, meticulous about planning always focusing on delivering the right solution.
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