PyData London 2024

Head of Data Science at Barclays UK

Aaron has developed numerous successful machine learning based products and capabilities across banks in Europe and Asia. His academic background is in physics and simulation science.

Adam Glustein is a Quantitative Developer at Point72 Asset Management in New York, USA. He is a contributor to CSP, a reactive stream processing library for both realtime and historical data.

I spent 10 years as an astrophysics researcher analysing high-energy data from space telescopes in the search for new objects in the universe and a better understanding of what we already knew to be out there. In 2015 I transitioned to data science joining a smart-cities startup called HAL24K. Over the next 8 years, I built data science solutions that enabled city governments and suppliers to derive actionable intelligence from their data to make cities more efficient, better informed, and better use of resources. During that time I built and led a team of 10 data scientists and helped the company spin out four new companies. In 2022, I joined ComplyAdvantage as a Senior Data Scientist working to combat financial crime and fraud.

I have been an active member of the PyData community since 2015 and founded PyData Southampton in 2023. I am also a long-time supporter of DataKind UK in their mission to bring pro-bono data science support to charities and NGOs in the third sector.

Alex Owens has been working in a combination of Python and C++ for the past 7 years. For the last 2 and a half of those, he has been a senior engineer and more recently tech lead on the new open-source Dataframe database, ArcticDB, which is backed by long-time Python enthusiasts Man Group and Bloomberg

Alexander is a software engineer working in cybersecurity at Palo Alto Networks. He first got into coding because he speaks Russian and wanted to automate reading endless Russian disinformation.

He cares about digital rights, inclusion in tech, writing safe code and contributing to the open source community.

When he isn't coding, he likes to drink at least 5 coffees a day and play basketball.

Alkiviadis is presently engaged as a Business Analyst at impruvo., an eBusiness consulting firm that specialises in consulting, recruitment, and technology services. He holds a bachelor’s degree in Marketing Communications, graduating with honours. Alkiviadis is currently pursuing a Master’s in Data Science and AI at the American College of Greece, where he has been awarded four scholarships for his academic excellence. He aims to integrate his master’s knowledge with the eCommerce industry. In addition, he harbours a passion for gadgets and succulent gardening.

A physicist by education and a lecturer of programming for data science and applied statistics for Milano Bicocca and Milano Cattolica universities, I worked as a data scientist to provide data-based business solutions. For example, my specialities include numerical optimization, NLP, Time Series analysis, signal analysis, and modelling projects.

I co-founded Apply Quantum (https://applyquantum.ai), specialising in AI, quantum computing, and providing training.

My technological stack includes a deep knowledge of R, Python, Unix environment, and Cloud infrastructures.

Andy Fundinger is a senior engineer at Bloomberg, where he develops Python applications in the Data Gateway Platform team and supports Python developers throughout the firm through the company's Python Guild. Andy has spoken several times at PyGotham, as well as other conferences such as QCon, PyCaribbean, and EuroPython.

In the past, Andy has worked on private equity and credit risk applications, web services, and virtual worlds. Andy holds a master's degree in engineering from Stevens Institute of Technology.

I lead CUDA Python Product Management, working closely with RAPIDS, Omniverse, and Math Libraries to unify NVIDIA's foundational offering for Python developers and the Python community.

I received my Ph.D. from the University of Chicago in 2010, where Ibuilt domain-specific languages to generate high-performance code for physics simulations with the PETSc and FEniCS projects. After spending a brief time as a research professor at the University of Texas and Texas Advanced Computing Center, I have been a serial startup executive, including a founding team member of Anaconda.

I am a leader in the Python open data science community (PyData). A contributor to Python's scientific computing stack since 2006, I am most notably a co-creator of the popular Dask distributed computing framework, the Conda package manager, and the SymPy symbolic computing library. I was a founder of the NumFOCUS foundation. At NumFOCUS, I served as the president and director, leading the development of programs supporting open-source codes such as Pandas, NumPy, and Jupyter.

I'm Anna-Lena, a machine learning engineer living in Bonn, Germany. I'm very passionate about learning and love to share my knowledge with other people. Besides machine learning I love teaching Python and have been a regular guest on PyCon events and podcasts. You can find my projects either on GitHub (https://github.com/zotroneneis) or on my personal webpage (https://alpopkes.com/).

I am an MLOps engineer at Simply Business; before that I worked as a data scientist for a market intelligence company and as a software developer creating web and mobile apps for insurance companies.

I hold a Masters Degree in Data Science and I also run a 17K subscriber YouTube channel about programming, machine learning and data science.

Product Lead of Data Scientist team in IT monitoring department of ING. PhD in Physics, BSc in Computer Science.

I am a Lead Data Scientist with over 8 years of experience. I have a passion for using data science to create innovative solutions, and led several high profile projects with significant business impact.

Carlos is a data scientist at IDInsight where he plays a key role in designing, testing, and improving various algorithms for partners.
Prior to joining IDinsight, he worked as a machine learning engineer for Gozem a ride-hailing startup based in Togo, implementing, improving and deploying machine learning models. He has also previously worked as a data scientist for the Togolese Ministry of Digital Economy, building dashboards.

Carlos holds a masters in Data Science from the Middlesex University of London and a bachelor’s in Mathematics and Computer Science at the Catholic University of Africa, Lome.

He has also co-authored a research paper studying extended category learning with Spiking Nets and Spike Timing Dependent Plasticity. Carlos is fluent in French, English and Ewe.

Cas Wognum is a machine learning engineer at Valence Labs. Within Valence, he has
contributed to several open-source projects in the datamol.io toolkit and is now leading
the Polaris project. He holds a MSc. degree in Artificial Intelligence and Computer
Graphics from the University of Utrecht.

Valence Labs is a research engine, powered by Recursion, committed to advancing the
frontier of AI in drug discovery.

After having a career in Data Scientist and Developer Relations, Cheuk dedicated her work to the open-source community and founded CMD Limes, a Python consultants cooperation. She has also co-founded Humble Data, a beginner Python workshop that has been happening around the world. She has served the EuroPython Society board for two years and is now a fellow and director of the Python Software Foundation.

Chi Wang is a principal researcher in Microsoft Research. He has worked on large language model and AI frameworks, automated machine learning, machine learning for systems, scalable solutions for data science and data analytics, and knowledge mining from text data and graph data (with a SIGKDD Data Science/Data Mining PhD Dissertation Award). Chi is the creator of AutoGen, a popular and rapidly growing open-source framework (with an Open100 award) for enabling next-gen AI applications. Chi is the creator of FLAML, a fast open-source library for AutoML & tuning used widely inside and outside Microsoft.

Chris is the Principal Quantitative Analyst in Baseball Research & Development for the Philadelphia Phillies. He is interested in computational statistics, machine learning, Bayesian methods, and applied decision analysis. He hails from Vancouver, Canada and received his Ph.D. from the University of Georgia.​

Chris is a Senior Data Scientist working in the Personalisation and Recommendations team at Tesco. Coming from a background in Physics, Chris joined Tesco though an internship programme as part of his MSc in Data Science and Machine Learning at UCL in 2022.

Dan is the Founder of Personify-AI, a startup specialising in building Chatbots for ecommerce.

Dan has spent 30 years working in technology in a varied career that has spanned development, management, consultancy and training.

Deb Nicholson is a free software policy expert and a passionate community advocate. She is the Executive Director at the Python Software Foundation which serves as the non-profit steward of the Python programming language. She has previously served the open source ecosystem through her work at the Open Source Initiative, Software Freedom Conservancy, and the Open Invention Network. She lives with her husband and her lucky black cat in Cambridge, Massachusetts.

Deepyaman is a software engineer at Voltron Data. Before their acquisition by Voltron Data, he was a Founding Machine Learning Engineer at Claypot AI, working on their real-time feature engineering platform. Prior to that, he led data engineering teams and asset development across a range of industries at QuantumBlack, AI by McKinsey.

Deepyaman is passionate about building and contributing to the broader open-source data ecosystem. Outside of his day job, he helps maintain Kedro, an open-source Python framework for building production-ready data science pipelines.

Principal software Engineer at Microsoft. Working on Polyglot Notebooks, .NET Interactive and actively collaborating with SemanticKernel and Autogen teams.

Matt joined the BBC as a Data Scientist in 2018 after spending several years as a post-doc modelling cloud microphysics in weather and climate systems. During the pandemic he developed an adaptive learning algorithm for BBC Bitesize to help GCSE students to revise while schools were closed. He spent 2021 working as the Experimentation Lead at the survey company Typeform - developing and scaling their experimentation capabilities. Since returning to the BBC, Matt has been focusing on marketing projects and causal inference and is currently using python and data to create personalised marketing assets for BBC iPlayer.

A pioneer of the data science revolution in the early 2010’s, Dr. Rebecca Bilbro is an applied AI/ML engineer, teacher, and author. Rebecca (aka @Elder_Data_Scientist on TikTok) is the co-creator of Yellowbrick, a Python library that integrates the scikit-learn and matplotlib APIs to support more convenient model diagnostics and steering. As co-founder and CTO of Rotational Labs (rotational.io), Rebecca is motivated by a desire to unite the data science and engineering communities. She and her team help other companies leverage in-house domain expertise and data to build and deploy LLMs, data products, and services. Rebecca earned her doctorate from the University of Illinois, Urbana-Champaign, where her research centered on domain-specific languages within engineering.

Elena is an Assistant Professor at Deree - The American College of Greece (ACG) and a Senior Artificial Intelligence (AI) Advisor with over 10 years of combined business, academic and lecturing experience in the fields of Machine Learning and Data Science.

Prior to her role with the American College of Greece, Elena was an Associate Director – Lead Data Scientist for the AI teams at HSBC Global Markets, UK, and Growth & Innovation at Alpha Bank, Greece. With a strong academic background in Computer Science and programming, Elena holds a PhD in Machine Learning & Data Mining, and is passionate about developing innovative solutions through data-driven strategies across various industries. She has also held several academic roles, conducting research for universities and institutes in Cambridge and London, and is a frequent speaker at machine learning conferences and events.

Elena’s work and research interests cover a broad range of AI applications with specialisation in Natural Language Processing (NLP), time series forecasting, recommender systems, and responsible AI (XAI, FAT-ML, AI Ethics), among others.

Emeli Dral is a Co-founder and CTO at Evidently AI, a startup developing open-source tools to evaluate, test, and monitor the performance of machine learning models.

Earlier, she co-founded an industrial AI startup and served as the Chief Data Scientist at Yandex Data Factory. She led over 50 applied ML projects for various industries - from banking to manufacturing. Emeli is a data science lecturer at Harbour.Space University, and a co-author of the Machine Learning and Data Analysis curriculum at Coursera with over 100,000 students.

A pharmacologist by training, and a software engineer by vocation. I'm a huge fan of all things that intersect using computers to solve biotech, medtech and healthcare problems.

Data Science student and BI Analyst at Public Power Corporation, Greece. Enthusiastic about discovering insights that drive strategic decisions.

Hajime is a data professional with five years of expertise in marketing, retail, and eCommerce, working in New York.

As a Data Analyst at Procter and Gamble and MIKI HOUSE Americas, Hajime has led data-driven strategy formulation and implemented technology initiatives such as e-commerce expansion, advertising optimization, and the identification of growth opportunities.

I have worked as a data scientist and BI developer for both the public and private sector in Canada. I have built Python applications in my day job including but not limited to: higher-education institutional teaching resource optimization for a major public research university, topic modeling for public opinion survey to facilitate better public policy making, risk detection in disease onset, record linkage to deduplicate fuzzy records in financial databases. I taught AI courses on a part-time basis for a public college post-graduate diploma program to better equip international students for North American analytics job markets. As a volunteer enthusiast to build up a local Python technology community, I also advocate for Python technologies together with AI modeling in founding the Public Data Technology Forum meetup group and running regular workshops since 2014, while running its corresponding YouTube tech talks channel too:

Public Data Townhall: https://www.youtube.com/channel/UCi6e2FiTbDrRdh90sPdCMXQ

Hendrik Makait is a data and software engineer building systems at the intersection of large-scale data management and machine learning. Currently, he works as an Open Source Engineer at Coiled, maintaining and improving Dask and its distributed execution engine. He lives in Hamburg, Germany.

Ian is a Chief Data Scientist, has co-founded and built the annual PyDataLondon conference raising $100k+ annually for the open source movement along with the associated 13,000+ member monthly meetup. Using data science he's helped clients find $2M in recoverable fraud, created the core IP which opened funding rounds for automated recruitment start-ups and diagnosed how major media companies can better supply recommendations to viewers. He gives conference talks internationally often as keynote speaker and is the author of the bestselling O'Reilly book High Performance Python (2nd edition). He has over 25 years of experience as a senior data science leader, trainer and team coach. For fun he's walked by his high-energy Springer Spaniel, surfs the Cornish coast and drinks fine coffee. Past talks and articles can be found at:

• https://www.linkedin.com/in/ianozsvald/
• https://ianozsvald.com/
• https://notanumber.email/
• https://github.com/ianozsvald/
• https://twitter.com/ianozsvald

Ines Montani is a developer specializing in tools for AI and NLP technology. She’s the co-founder and CEO of Explosion and a core developer of spaCy, a popular open-source library for Natural Language Processing in Python, and Prodigy, a modern annotation tool for creating training data for machine learning models.

Jacob Tomlinson is a senior software engineer at NVIDIA. His work involves maintaining open source projects including RAPIDS and Dask. He also tinkers with kr8s in his spare time. He lives in Exeter, UK.

Jeroen is a Machine Learning Engineer at Xebia Data (formerly GoDataDriven), in The Netherlands. Jeroen has a background in Software Engineering and Data Science and helps companies take their Machine Learning solutions into production.
Besides his usual work, Jeroen has been active in the Open Source community. Jeroen published several PyPi modules, npm modules, and has contributed to several large open source projects (Hydra from Facebook and Emberfire from Google). Jeroen also authored two chrome extensions, which are published on the web store.

Hope to see you at PyData London 🇬🇧! 👋🏻

Jetze is a well-rounded Machine Learning Engineer who is as comfortable solving Data Science use cases as he is productionizing them in the cloud. His interests include MLOps, GenAI and Cloud Engineering. As a researcher, he has published papers in Computer Vision, Natural Language Processing and Machine Learning in general. Jetze loves sharing knowledge during community events and by giving trainings.

Jim Dowling is CEO of Hopsworks and an Associate Professor at KTH Royal Institute of Technology. He is lead architect of the open-source Hopsworks Feature Store platform. He is currently writing a book for O'Reilly on "Building ML Systems: batch, real-time, and LLMs"

John Sandall is the CEO and Principal Data Scientist at Coefficient.

His experience in data science and software engineering spans multiple industries and applications, and his passion for the power of data extends far beyond his work for Coefficient’s clients. In April 2017 he created SixFifty in order to predict the UK General Election using open data and advanced modelling techniques. Previous experience includes Lead Data Scientist at YPlan, business analytics at Apple, genomics research at Imperial College London, building an ed-tech startup at Knodium, developing strategy & technological infrastructure for international non-profit startup STIR Education, and losing sleep to many hackathons along the way.

John is also a co-organiser of PyData London, co-founded Humble Data in 2019 to promote diversity in data science through a programme of free bootcamps, and in 2020 was a Committee Chair for the PyData Global Conference. He is currently a Fellow of Newspeak House with interests in open data, AI ethics and promoting diversity in tech.

Juan Luis (he/him/él) is an Aerospace Engineer with a passion for tech communities, outreach, and sustainability. He works at QuantumBlack, AI by McKinsey, as Product Manager for Kedro, an opinionated Python framework for creating reproducible, maintainable and modular data science code. He has worked as Developer Advocate at Read the Docs, as software engineer in the space, consulting, and banking industries, and as a Python trainer for several private and public entities.

Apart from being a long-time user and contributor to many projects in the scientific Python stack (NumPy, SciPy, Astropy) he has published several open-source packages, the most important one being poliastro, an open-source Python library for interactive astrodynamics used in academia and industry.

Finally, Juan Luis is the founder and former chair of the Python España association, the point of contact for the Spanish Python community, former organizer of PyCon Spain, which attracted 800 attendees in its last in-person edition in 2022, and current organizer of the PyData Madrid monthly meetups.

Richard is an Experienced Senior Software Engineer, who has a lot of experience developing and deploying AI applications.

Kishan is a machine learning and data science lead, course instructor, and open source software contributor. He has contributed to well known Python packages including statsmodels, Feature-engine, and sktime. He has 10+ years of experience in applying machine learning and statistics in finance, e-commerce, and healthcare research. He leads data science teams to deliver data and machine learning products end-to-end.

Kishan attained a PhD in Physics from Imperial College London in applied large scale time-series analysis and modelling of cardiac arrhythmias; during this time he taught and supervised undergraduates and master's students.

LinkedIn: https://www.linkedin.com/in/kishanmanani/

Medium: https://medium.com/@kish.manani

Twitter: https://twitter.com/KishManani

GitHub: https://github.com/KishManani

Konstantinos holds a Bachelor of Science in Physics with a major in Astrophysics from the National and Kapodistrian university of Athens. He is currently pursuing a Master's degree in Data Science at the Deree College honing his skills in programming, machine learning and AI. Proficient in Python and mathematics, Konstantinos excels in analytical problem-solving and agile methodologies. In his free time, amongst other hobbies, he enjoys staying informed and acquiring knowledge on cutting-edge technology.

ML Engineer

Marco is a core dev of pandas and Polars and works at Quansight Labs as Senior Software Engineer. He also consults and trains clients professionally on Polars. He has also written the first Polars Plugins Tutorial and has taught Polars Plugins to clients.

He has a background in Mathematics and holds an MSc from the University of Oxford, and was one of the prize winners in the M6 Forecasting Competition (2nd place overall Q1).

CTO & Co-Founder at Spiral

Spiral is a small startup based in London and New York building a new database to accelerate machine learning and tabular analytics.

Nick Radcliffe is a practising data scientist with over 30 years experience, from neural networks (a.k.a. deep learning) and genetic algorithms on parallel systems in the late 1980s, through parallel machine learning and 3D visualisation software as a founder of Quadstone, from 1995, to novel modelling methods (e.g. uplift modelling) in the early 2000s. Since 2007, he has run Edinburgh data science specialists Stochastic Solutions Limited.

Nick uses his deep knowledge of underlying algorithms to fashion tailored solutions to practical business problems for clients including Barclays, Sainsburys, T-Mobile and Skyscanner, and was a key developer of Uplift Modelling—a method for modelling the differential effect of a treatment across a population.

Over recent years, he has developed a particular focus on testing data and data processes for correctness, developing and applying a methodology and set of tools known as test-driven data analysis (TDDA), with open-source and proprietary variants. These will feature in talks and training sessions in this year's DataFest.

Nick is also a Visiting Professor in the Department of Mathematics at the Edinburgh University and organises the PyData Edinburgh monthly meetup, which regularly brings together around 100 data scientists.  He has acted as an adviser and consultant to various firms including SEP and Fluidinfo and has co-authored two books.

I am an Engineering Manager (for Data Science projects) at Sicara, where I worked on a wide range of projects mostly related to vector databases, computer vision, prediction with structured data and more recently LLMs.
I am currently leading the GenAI development in the company.
You can find all my talks and articles here: https://www.sicara.fr/en/noe-achache

Patrick Hoefler is a member of the pandas core team and a Dask maintainer. He is currently working at Coiled where he focuses on Dask development and the integration of a logical query planning layer into Dask. He holds a Msc degree in Mathematics and works towards a Msc in Software engineering at the University of Oxford.

Nafiul Islam is a Software Engineer, Speaker and Author. With more than a decade of development experience, Nafiul loves talking about developer experience and how to make it better. Nafiul currently works at Sonar as the Developer Advocate for Python. Previously, he worked at JetBrains and Microsoft.

Raymond Cunningham is a builder of distributed systems with 20+ years of experience in a number of different startups that he either co-founded or was one of the first employees. Currently, along with the Hopsworks engineering team, he is building a best in class MLOps platform and feature store to accelerate the delivery of cutting edge machine learning solutions.

Rhythm Patel is a software engineer at Bloomberg. He is a part of Bloomberg's Python Guild, which is dedicated to aiding Python engineers, fostering innovation, creating and maintaining Python packages, as well as acting as a bridge to the wider Python community. Rhythm has spoken at PyCon US 2024, PyCon Italy 2024, PyCon Germany 2024, PyCon UK 2023, and other internal events. When he’s not working, you can find him playing football or tennis, traveling and hiking, or volunteering at London’s Royal Parks and London Zoo.

This is Sefik.

I received my MSc in Computer Science from Galatasaray University in 2011.

I have been working as a software engineer since 2010.

Currently, I live and work in the financial district in London, UK but I am a true Istanbulite at heart.

My research interests are Machine Learning and Cryptography. I’ve published several research papers about these motivations. Also, I enjoy speaking to communities about these disciplines.

Moreover, I enjoy to contribute open source projects. Explore my GitHub repository to discover some notable projects, including DeepFace—a lightweight face recognition and facial attribute analysis library for Python, boasting 9K stars; RetinaFace—an lightweight Deep Face Detection Library for Python with 854 stars; and ChefBoost—a lightweight boosted decision tree library for Python, celebrated with 431 stars.

I am a machine learning and NLP engineer who firmly believes in the power of data to transform decision making in industry. I have a Master in Computer Science (software engineering) and a PhD in Sciences (Bioinformatics), and more than 16 years of experience in Natural Language Processing and Machine Learning, including in the pharmaceutical industry and the food industry. Since 2019, I have been a core maintainer of spaCy, a popular open-source NLP library created by Explosion. Additionally, I work as a consultant through my company OxyKodit. Throughout my code and projects, I am passionate about quality assurance and testing, introducing proper levels of abstraction, and ensuring code robustness and modularity.

Stamatis is the Co-founder of Asappien, an application aimed at addressing post-pandemic social and digital isolation. Currently employed as a CRM Data Analyst at Aegean Airlines, he holds a bachelor's degree in finance with distinction. Pursuing a Master's in Data Science and AI at the American College of Greece, Stamatis has earned triple scholarships for his academic excellence. He is deeply passionate about traveling, mathematics, and artificial intelligence.

Sultan is an experienced data scientist with proven records of delivering business solutions and data products through the application of AI, predictive modeling, and advanced analytics.

He is rigorous about collaborating with technical and non-technical stakeholders to transform data into meaningful business insights, ultimately enabling commercial advantages.

Sultan is also a ML Subject Matter Expert (SME) at Amazon Web Services and technical author at Towards Data Science (TDS), skilled in machine learning, data engineering, natural language processing, deep learning, and statistics.

He has a master's degree in Business Analytics from University College London.

Beyond his professional pursuits, Sultan has interests in traveling, hiking, and Tag Rugby.

Tania is the director of Quansight Labs, an organization that builds and maintains sustainable open-source projects and communities, mainly within the PyData ecosystem. She is also a director of the PSF (Python Software Foundation) and a member of the PyLadies Global Council. She is passionate about open source, its community, and building tools for developers and data scientists.

Founder & CEO of PyMC Labs. Co-author of PyMC.

Tun Shwe is the VP of Data at Quix, where he leads data strategy and developer relations. He is focused on helping companies imagine and implement their strategic data vision with stream processing at the forefront. He was previously a Head of Data and Data Engineer at high growth startups and has spent his career leading T-shaped teams in developing analytics platforms and data-intensive AI applications.

In his spare time, Tun goes surfing, plays guitar and tends to his analogue cameras.

Victor Dibia is a Principal Research Software Engineer at the Microsoft Research AI Frontiers organization where his focus is on Generative AI and applied machine learning. His research has been published at conferences such as EMNLP, AAAI, and CHI and has received multiple best paper awards. His work has also been featured in outlets such as the Wall Street Journal and VentureBeat. He is an IEEE Senior member, a Google Certified Professional ( Data Engineer, Cloud Architect ) and currently a Google Developer Expert in Machine Learning.

I have been in love with mathematics, physics, and music since childhood, and I started programming at the age of 15 - I have been fascinated by data science ever since. I'm also a guitar player and a performing chorister, now exploring the possible connections between music and data science.

I am currently a student of Computer Science at the Faculty of Mathematics and Information Science at Warsaw University of Technology. Since August 2023, I have been working as a Data Scientist at Piano for AI, where I combine my passions for music, mathematics, and data science. I develop software for training and evaluating large language models on musical data, among other fascinating projects.

Lex Avstreikh is a machine learning strategist with a solid track record in enhancing operational systems and advancing ML infrastructure technologies. At Hopsworks, he is part of the team in charge of designing new innovative capabilites, leveraging his expertise in MLOps, to establish strong market positions against industry giants. Lex is also contributing to the use of F.A.I.R. principles in multiple research projects accross Europe.