The International Community of Practice for Data Analysts, Scientists, and Engineers
The Data Science Expert Group is an international community of practice for media professionals working in data science, data analytics, and data engineering in the newsroom. Members interact and regularly learn together, sharing a repertoire of resources, experiences, stories, tools, and ways of addressing recurring problems.
Our goal is to arm practitioners with insights, feedback, and tools aligned with newsrooms’ priorities to grow audiences, deepen user engagement, and optimise reader revenue.
We share case studies, ideas, resources and connections that help spread good practices.
Members are invited to monthly meetups to explore operational challenges around practical business cases. The Group’s online forum helps create a community of practice beyond regular group meetings, sharing valuable resources and sparking collaboration and discussion between members. See who our members are.
WHY JOIN
Our community of practice connects like-minded data experts and creates an avenue to interact, pool resources, and work in partnership:
Exchange information and knowledge to keep innovate;
Keep your technology skills current and develop a new skill set to deepen your job satisfaction;
Solve emergent or urgent problems by calling on the strenght of a peer-to-peer collaborative network.
WHAT’S IN IT FOR YOU
ELIGIBILITY & COMMUNITY GUIDELINES
Our community of practice is tasked with setting up a crowdsourced knowledge-sharing platform where members can find the content they need and share information that will benefit others.
Participants are required and encouraged to contribute to enhancing the experience of all participants and encouraging enthusiasm for learning, intellectual honesty, vigour in debate, and openness.
- Members work in data science, analytics, engineering, data “leadership,” or a related domain. They are news media professionals actively engaged in the evolution of data analytics and actionable metrics to help publishers and newsrooms understand what their audiences value and what engages them.
- Members of the Data Science Expert Group work for a news organisation and are members of WAN-IFRA. Are you not yet a member, or unsure if you are a member? Fill in the “Join the Data Science Expert Group” form below, and we’ll get back to you immediately.
- Members are willing to share experiences with industry peers to grow common knowledge. They commit to providing at least one contribution per year on the occasion of the Group’s working sessions and roundtable discussions. We are running our meetings under the “Chatham House Rule”: participants can use ideas from the sessions, but they are asked not to attribute specific comments to other participants.
CALL FOR SPEAKERS
Are you interested in sharing a use case, recommending a session topic, speakers or companies, or would you like to share any other comments?
PAST EVENTS
Advertising Data Intelligence : From quality insurance to revenue generation at Axel Springer
The purpose of this meetup was to present Axel Springer Media and Tech’s incremental revenue analysis project, which was designed to evaluate the added value of different programmatic advertising partners and identify revenue optimisation opportunities through data analysis. Fixing the identified bugs reduced negative incremental revenue from 4% to below 1% of auctions
Synthetic Audiences and Personas for news product development and testing
The core idea behind “synthetic audiences” is that news organisations struggle to centre their audience due to resource constraints, which makes audience research expensive. AI offers a dynamic solution through digital twins that simulate audience responses, reusable across various questions without constant human interaction, provided ethical and bias concerns are addressed.
The Data Science Day hosted by Süddeutsche Zeitung in Münich includes practical use cases, hands-on workshops, thematic round table discussions, and bespoke networking opportunities.
“Augmented Journalism”: Predicting how articles perform at Le Télégramme
Yoann Péron, Data Science Manager at Le Télégramme, presented a project on “augmented journalism”, a collaboration between the French local newspaper and IRISA research centre, aimed at helping journalists improve their articles by providing information on their potential success and suggesting ways to enhance them and understand the different capacities of their articles and how to improve them for various platforms.
Getting new ML models into production with ease
Ashraf Ahmed, Enterprise Architect at Mather Economics, discusses the challenges of scaling machine learning operations, including lack of established guidelines, difficulty measuring data quality, and managing large volumes of data and models with limited resources. He emphasised the importance of efficient data modelling with tools like flexible catalogues and data tiering, continuous model delivery with version control, safe experimentation through policy systems and data collection, and a deliberate architecture design separating concerns between data scientists and system engineers.
REPLAY MORE USE CASES
