Yext makes software and tools to improve everyone’s experience on the internet
by providing perfect answers everywhere. Our clients trust us to use natural
language processing (NLP) and machine learning (ML) to deliver correct
information to end users everywhere.
As a Senior Data Scientist you will shape algorithms to develop essential
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.
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
- Solve data science problems end-to-end, starting from exploration and analysis to pragmatic implementations of high quality solutions
- Effectively communicate quantitative results in a timely manner (you will be responsible for producing exceptional written and visual documentation)
- Write high quality Python code (we use PyTorch, Transformers in many places)
- Mentor junior team members, provide technical leadership and execution guidance
- Exercise excellent technical judgment and prioritization around complexity, completeness, details and risks
- Communicate data science and machine learning concepts to a variety of audiences (product managers, software engineers, executives, sales partners).
- Partner with product management and engineering teams throughout the product development lifecycle
What You Have
- Advanced degree in a quantitative discipline, e.g., computer science, mathematics, physics, statistics, applied mathematics, economics, or operations research
- 5+ years of quantitative/research experience
- Autodidactic, Self directed – You are able to dive into a new unfamiliar problem domain and learn quickly in the face of adversity – You are comfortable with uncertainty and project evolution
- Highly developed communication skills (writing and figures)
- Experience leading cross-functional agile work streams and scaling data-driven initiatives
- Multi-tasking, project management, and leadership skills.
- Experience in Tensorflow or PyTorch, and state-of-the-art transformer/NLP models and techniques (e.g. FastText, BERT, et al.).
- NLP experience, especially with sentence embeddings.
- Very experienced in Snowflake, MySQL, and Presto.
- Excellent ability to solve "glue" problems (e.g. shell scripting, python environment setup, efficient programming practices)
- Experience with common quantitative analysis and ML packages (in Python or R) such as Pandas, Matplotlib, ggplot, scikit-learn and scipy.
- Experience with JVM languages (Java, Scala) a plus. GoLang or C++ also great!
- Experience with AWS, Linux and Mac environments
- 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)
The base salary at the time of hire for this position is expected to be
between $149,850 - $249,500. Pay ranges at Yext are established based on an
analysis of salaries for positions with a similar level of accountability and
impact in the relevant labor market. Salary levels are expected to change to
reflect an employee’s job performance (results and impact) over time. Salaries
at the time of hire are typically offered in the lower to middle of the above-
referenced range in order to provide the opportunity to reflect performance-
based increases over time. In addition to base salaries, employees at Yext are
typically eligible for a comprehensive package of benefits, and successful
candidates may also be eligible for equity (stock) based compensation and/or
variable pay programs based on performance relative to goals and targets.