Jodie Burchell, Phd Email & Phone Number

Berlin, De

Prague, Hlavní Město Praha, Cz

Prague, Hlavní Město Praha, Cz

I am currently the developer advocate in data science at JetBrains. In my role, I have two key functions. The first is to advise multiple product teams (PyCharm, Datalore and JetBrains AI) about the principles of data science, and help guide data science features in these products. The second is to raise the profile of JetBrains as a data science company in the community. In this role, I have done the following:• Guided the introduction of IDE features which make working with major new data science libraries easier. The most notable of these was Polars DataFrames and Hugging Face model cards.• Helped development teams improve existing features important to the data science workflow, including DataFrame support, Jupyter debugging and remote development.• Acted as an internal advisor on data science topics to key staff at JetBrains. In particular, due to my experience with NLP and LLMs, I have helped educate these coworkers about the technical details underlying our AI coding assistant.• Have established myself as an international keynote speaker on machine learning, NLP and LLMs. I have spoken at more than 20 conferences in the past two years, including PyCon US, EuroPython and ODSC West. This year, I keynoted for NDC Porto and PyCon Italia.• Have been invited to speak on 16 external podcasts on a broad range of data science topics, from data science tooling to AI coding assistants.• I am a co-organiser of a community workshop (Humble Data) designed to mentor people new to data science. I have run two successful workshops at EuroPython and with PyLadies Berlin, and will be running four more in the coming months at major PyCons.• I work entirely remotely on a team distributed across Europe and the United States.

New York, Ny, Us

I worked as the Data Science Lead of audiences generation at Verve Group. This involved driving the technical direction of audience products, which allowed the company to categorise mobile device users for the purposes of targeting advertisements.• I built privacy-first audiences to predict a mobile device user’s age and gender for the ATOM project, which generate predictions on the device and therefore do not require sending PII to a centralised server.• I created a POC of a model that predicted which ad requests were unlikely to generate revenue. This model is projected to drop 30% of requests while retaining 99% of revenue, leading to ~$4,500 savings in compute costs per day.• I managed a mid-level data scientist, and conducted technical interviews for this and three other data science positions. I also mentored a BI Analyst to transition to a data science role in the company.• I worked with colleagues in five different countries, including having half of my team and my manager located in the United States.

New York, Ny, Us

Düsseldorf, North Rhine-Westphalia, De

As a data scientist in the Search and Match team, I worked with product owners, software developers, data scientists and linguists to improve the site’s search functionality. In this role, I delivered a number of major projects:• I wrote an application in Python that automatically mines potential new job titles and skills every month for curation by linguists. This software has been put into production and currently runs monthly, processing over 1 billion rows of data stored on Redshift monthly.• I built a machine learning model on ~4.5 million job offers, which accurately and quickly predicts job titles from skills and vice versa in four languages. I helped to put the model in production and optimise it using Java. This is currently being used to improve the quality of a job recommendation product which is sent to candidates on a daily basis. It will also be integrated into our search engine to improve the quality of the results.• I made a proof-of-concept to extend our search engine to return better results for rare queries. This proof-of-concept used cutting edge text embedding models.I also worked closely with my team to complete other data science projects, includingseveral products that have improved search using personalisation.

Cremorne, Victoria, Au

I worked closely with analysts, data scientists and product/strategy managers to develop data products for SEEK and their partner sites. One of my main projects was extending the coverage of the site’s job recommender, where I created three algorithms that provided additional recommendations to ~2.5 million candidates per week, as well as reaching ~40,000 candidates who had not been previously receiving recommendations.Another major project that I worked on was the creation of a related-search algorithm, which suggested additional keywords to candidates based on their original search term. This product was rolled out across 9 countries, and greatly improved the search experience for candidates.

Melbourne, Victoria, Au

The focus of my postdoctoral fellowship was biostatistics and epidemiology, and the majority of my role was working directly with data mining and complex statistical analysis across a range of domains. Two of my key projects used all data from an Australian state’s hospitals (~25 million observations). The first project analysed cardiac care and won a very competitive research grant (5 winners of 580 applicants Australia-wide). The second described end-of-life care for cancer patients and formed the basis of a Melbourne-wide palliative care program for these patients.Much of this role focused on building and interpreting statistical models to explain how these patient populations interacted with the hospital system, and how this system could better meet their needs. Part of this work has now been published in Annals of Internal Medicine, one of the top medical journals in the world. In addition, I am author on another 9 journal articles resulting from work completed in this role.

Au

I project managed a study assessing the use of psychological support with cancer patients, which I completed on time and under budget. I completed all data collection, entry, cleaning and analysis (in Stata and R). In addition, I created all project materials, which ranged from a therapy manual to a journal publication.

Canberra, Australian Capital Territory, Au

I wrote SPSS syntax to manipulate and analyze HILDA, a large longitudinal data set (~10, 000 entries). I completed a cluster analysis to identify subpopulations with different mental health needs. This analysis was used as the basis of a further project.

Doctor Of Philosophy (Ph.D.), Psychology

Bachelor Of Science (B.Sc.), Psychology

Bachelor Of Science (B.Sc.), Ecology And Evolutionary Biology