We’re hiring a data scientist.
By: Local News Lab, Brown Institute
Tags: Jobs, Data Science, Journalism, Hiring, Machine Learning

Come help us build products at the intersection of technology, journalism and revenue to help sustain local news.

Photo by Henri Mathieu-Saint-Laurent from Pexels

We are a small but mighty team and we’re thrilled to announce we are hiring a Data Scientist for a 3-month contract with potential to extend. The posting is below (and you can apply via this link), but first, a little more about us.

As 2020 comes to a close, it’s important to recognize the vital work that local newsrooms have been doing, keeping us informed and safe through the COVID-19 pandemic and all the other major — and minor — news events of the year. At the Brown Institute’s Local News Lab, we have been working hard developing partnerships and technology to support these organizations. Our mission is to provide them with insights and products to optimize audience engagement and drive subscriptions (or donations or memberships) that ultimately help ensure their sustainability and survival.

Position Summary

The Local News Lab is a team of engineers, designers, data scientists, and journalists, working to build AI-powered, open-source products to help support local newsrooms and their businesses. We are located within the Brown Institute for Media Innovation at the Columbia Journalism School.

The Local News Lab is committed to developing and building solutions that center local newsrooms. Our team has over two decades of combined experience working in media, helping attune us to the ethical sensitivities in journalism. An Advisory Board of roughly a dozen representatives from both large and small newsrooms ensures we have input from a range of perspectives, as we move from experimentation to prototyping and production. Finally, we have a Partnerships Lead who is dedicated to the task of nurturing our newsroom relationships, so we can engage in ongoing dialogue and avoid an extractive, parachuting approach to our work.

As the first of a number of anticipated projects, we are developing an open-source smart paywall that deploys Machine Learning (ML) to go beyond one-size-fits-all solutions to audience engagement. We explicitly extend the idea of a paywall to include a variety of actions that a publisher can take to engage their readers and encourage subscription or donation. Currently, our team is exploring three avenues of data science work — paywalling likely subscribers, selecting premium content, and personalizing reader recommendations. We are looking for a data scientist to begin work on novel approaches, in addition to deepening this existing research. The end goal of this work is to deploy equitable and explainable models that help local newsrooms sustain their businesses.

Our team strives not only to produce equitable technology, but to work in as equitable a manner as possible. We make a concerted effort to distribute the administrative and emotional labor that often falls too heavily on those who are not cis men. We try our best to be inclusive of all genders and to make space for our POC and femme teammates during meetings and in decision-making processes. We don’t always get it right, but we hope to create an environment where everyone is comfortable sharing their feedback when we don’t.

Responsibilities

Develop pipelines that extract insights from news text and clickstream data in order to:

Enable newsroom strategists to make more informed decisions

Facilitate automatic decision-making, including, but not limited to, paywalling likely subscribers, selecting premium content, or personalizing reader recommendations

The successful candidate will be primarily responsible for the statistical components of the system and will serve as an authority on the topic among the development team members. Under the supervision of the Project Lead, the Data Scientist, together with the full development team, will hone the project’s formal specifications, and set technical milestones.

This is an externally funded position, contingent on performance and the continued availability of funding.

Qualifications

The ideal candidate has experience in one or more of the following domains:

NLP: entity extraction, resolution, and linking. Linguistic pattern analysis, such as LIWC, readability, sentiment. Topic modeling, such as LDA, text clustering

Network analysis: community detection, influence analysis

Experiment design: crowdsourcing, conducting and evaluating A/B tests

Reader analytics: experience optimizing metrics like impressions, CPM, conversions

Data science ethics: statistical fairness, model explainability, auditing for bias

Experience with software for newsrooms and the news industry is desirable but not required.

Feel free to contact our Project Lead, Al Johri if you have any questions about the role.

Click here to apply.