Senior Data Scientist
New York, NY
Yext (NYSE: YEXT) is building the next big thing in AI search, and the next big thing is answers.
With the explosion of information and data online, search has never been more important. However, while the world of consumer search has innovated over time, enterprise search has not. In fact, the majority of enterprise search is powered by outdated keyword technology that only scans for keywords and delivers a list of hyperlinks rather than actually answering questions. Yext, the AI Search Company, offers a modern, AI-powered Answers Platform that understands natural language so that when people ask questions about a business online they get direct answers – not links.
We have a big, audacious mission to transform the enterprise with AI search. To achieve that, we need bright minds and diverse perspectives to join our growing company and help us continue to disrupt an industry. Does this sound like you?
As a Senior Data Scientist you will craft how data is collected, transformed, and used to develop crucial new capabilities and features for Yext’s products. We manage large amounts of structured master data on behalf of some of the world’s largest companies and collect transactional data through end-user-facing applications we host directly for these clients. Our mission revolves around deeply understanding user intent, so we can deliver relevant and accurate answers to questions, everywhere people search.
Yext clients cover a tremendous breadth of industries. We are seeking data scientists excited to discover opportunities in data across a wide variety of business domains. You will work collaboratively with cross-team partners in software engineering, product management, and strategy. This approach will allow you to participate fully in the product development lifecycle and make pragmatic decisions about the design, training, and deployment of machine learning models driving key product features!
What You'll Do
- Partner with product management and engineering teams throughout the development lifecycle
- Solve full stack Data Science problems – Implement solutions to a data science problem in a production environment, coping with all the challenges (such as data cleanliness, performance, unexpected feedback loops, and concept drift) that arise
- Articulate Data Science and machine learning concepts to a variety of audiences (product managers, software engineers, executives, sales partners)
- Mentor junior team members, provide technical leadership and execution guidance
- Dive deep into the details when called for while demonstrating good judgement about when to simplify and prioritize
What You Have
- Advanced degree in a quantitative field, e.g., computer science, mathematics, business analytics, statistics, applied mathematics, economics, or operations research, or similar college level education
- Knowledge of neural network packages (TensorFlow, PyTorch) and state-of-the-art transformer/NLP models and techniques (e.g. FastText, BERT, et al.)
- 5+ years of work experience working in a Data Scientist Role
- Autodidactic, self-directed – Ability to dive into a new unfamiliar problem domain and start learning about it – You are comfortable with uncertainty and project evolution
- Effective communicator, a good writer, and know effective means of visually displaying quantitative information
- Experience leading multi-functional agile work streams and scaling data-related initiatives
- Proficiency with data analysis software and tools such as Python and SQL
- Outstanding multi-tasking, project management, and leadership skills
- Experience with JVM languages (Java, Scala) a plus. GoLang or C++ also great!
- Experience with AWS, Linux and Mac environments
- Excellent ability to cope with glue problems - shell scripting, debugging python environment problems, fixing broken packages
- Knowledge of Python or R, and the machine learning, data processing and visualization packages (e.g. Pandas, Numpy, scikit-learn, Matplotlib)
- Knowledge of SQL and databases like MySQL, Postgres, Presto and Hive.
- Knowledge of statistics and good experimental practices (e.g. how to run a powerful A/B test and test for significance)
- Knowledge of techniques in unsupervised machine learning and information retrieval and mining (e.g. DBSCAN, k-Means, indexes)
Yext is committed to building an inclusive and diverse culture where every person is seen, heard and valued. We believe in equal employment opportunity and welcome employees and applicants of all races, colors, ethnicities, religions, creeds, national origins, ancestries, genetics, sexes, pregnancy or childbirth, sexual orientations, genders (including gender identity or nonbinary or nonconformity and/or status as a trans individual), ages, physical or mental disabilities, citizenships, marital, parental and/or familial status, past, current or prospective service in the uniformed services, or any characteristic protected under applicable law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a reasonable accommodation in completing this application, interviewing, or participating in the employee selection process, please complete this form.