Data Scientist (Relevancy Ranking Algorithms)
Technology | Seattle
Getty is embarking on its next wave of innovation in visual storytelling and how to put the perfect image or video in our customer’s hands, be it for a society-changing headline or a brand’s next big campaign—truly moving the world with images.
We are looking for a Data Scientist with expertise in ranking algorithms (search, recommendations, and/or newsfeeds) to join our AI/ML Team to research, experiment, and introduce new machine learned ranking models to Getty’s search experience. You will have a direct impact on the Search and Browse paths for millions of customers and drive key conversion metrics.
You’ll have access to a growing, rich dataset of the most trusted, esteemed, and diverse visual content in the world with over 250 million award-winning images and videos encompassing the latest global news coverage from red carpet events to football stadiums to conflict zones; exclusive conceptual creative images; and the world’s largest commercial archive. With a global presence, our search interaction data comes from over 50 million unique visitors a quarter from almost every country in the world.
What you’ll be doing:
Research and build machine learning algorithms for search ranking leveraging our images, metadata, and/or customer interactions to significantly improve our customer’s image/video finding and discovery experiences.
- Recommend changes to our search ranking strategy presented in a clear manner to team members and leadership
- Develop and implement online and offline testing and validation methodologies
- Partner closely with other data scientists, data engineers, machine learning engineers, and search engineers to implement and deploy new ranking algorithms in production
- Collaborate closely with product, search engineering, and data science leaders
- Share your expertise by mentoring others on the team
We’d love to hear from you if:
- Proven experience building and validating ranking, recommendation, and/or newsfeed algorithms for customer-facing products.
- A strong understanding of the real-world advantages and drawbacks of various ranking algorithms and measures of success.
- Hands-on experience with accessing data, Python, machine learning libraries, and deep learning libraries (ex: scikit-learn, numpy, pandas, scipy, tensorflow, SQL, hive, spark, etc.). Nice-to-have: experience with search technologies such as SOLR, Learn-to-rank, and nearest neighbor maps of deep learned embeddings (ex: FAISS).
- You write clean, understandable code that follows best practices, is well-documented, and build easily reproducible models
- You are excited to dig into the context in which data was generated to consider biases that may exist in the data, and make appropriate considerations in developing solutions
- Excellent communication skills. You are a good listener open to many diverse voices and perspectives. You are transparent, trustworthy, and honest.
- Ability to independently execute on a project, from ideation to testing to delivery, and can pro-actively interact with other engineers to access necessary resources or data.
- A Ph.D. or MS in Computer Science, Statistics, Data Science, Mathematics, Economics/Sconometrics, Sociology, Natural Sciences or any other equivalent quantitative field is preferred. If you are self-taught and believe you are a good fit for this role, or have significant work experience, we would love to hear from you as well.
Getty Images is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. Getty Images believes that diversity is critical to our success in moving the world with images and is committed to creating an inclusive, mutually respectful environment which celebrates diversity. We seek to hire on the basis of merit, competence, performance, and business needs.