Data Scientist Computer Vision at Thorn

(Will also consider senior level candidates with computer vision experience.)
Thorn is a non-profit focused on building technology to defend children from sexual abuse. Working at Thorn allows you to apply your skills, expertise, and passions to directly impact the lives of vulnerable and abused children. Our staff solves dynamic, quickly evolving problems with our network of partners from tech companies, NGOs, and law enforcement agencies. If you can operate well in a complex and quickly changing environment and are able to talk specifically about heavy issues while bringing positivity to your work and colleagues, you could be an excellent fit for our team. 
In 2019, we took the stage at TED and shared our audacious goal of eliminating child sexual abuse material from the internet. A key aspect of our work is keeping abreast of the new ways technology is used to sexually exploit and abuse children and building the right technology in response to combat this, as well as building technology to support the broader child safety ecosystem in combating online child sexual abuse.
About the role:
As a Data Scientist, you build machine learning models to add intelligence to your team's product. You will uncover valuable insights, to expand and build on our existing and future products. The work you will do will be a combination of finding quick wins and developing longer term research. You will collaborate closely with Engineering and Product to identify insights and build models that will make an invaluable impact. You will be responsible for acquiring data, crafting and performing analytical experiments in a disciplined manner, evaluating and iterating on results, and discussing results with your team. When you and the team conclude that the model or insight is ready to be shipped, you will partner with members of the Engineering team to simplify, architect, and implement an infrastructure for continuous deployment.
What You'll Do:

Research and develop statistical modeling for data analysis.
Build machine learning models to help end online child sexual abuse.
Provide business analysis to help streamline workflows.
Collaborate with team members to drive understanding of product and technology standards needs and devise possible solutions.
Discuss results and ideas with key partners, including child victim identification specialists, relevant law enforcement, and technology companies.
Implement new statistical methodologies as needed for specific models or analysis, prioritizing fairness in design and build.
Work with Data Science and Engineering team members on deploying insights and models and continuous model training and deployment. 
Keep up-to-date with the newest developments in data science and machine learning.

What We’re Seeking:

A commitment to putting the children we serve at the center of everything you do.
You have experience designing, building, and deploying computer vision (traditional and deep learning) applications for production use cases.
You have a background in data science and statistical analysis.
You have an ability and interest in learning new technologies quickly.
You have a passion for machine learning and an aptitude to work in a collaborative environment, can demonstrate empathy and strong advocacy for our users, while balancing the vision and constraints of engineering.
You communicate clearly, efficiently, and thoughtfully. We’re a highly-distributed team, so written communication is crucial.

Technologies we use:
You should have at least one year of professional experience with these:

Tensorflow or PyTorch
OpenCV (or equivalent image manipulation library)

You should have non-trivial experience with at least a few of these, but we’re open to teaching folks that have the desire and ability to learn the rest.

Pandas
Scikit Learn
Spacy, HuggingFace for NLP
Jupyter

At Thorn, we understand the value of developing a team with different perspectives, educational backgrounds, and life experiences. We prioritize diversity within our team and encourage people from underrepresented backgrounds to apply. Your skills are needed here.