Senior Applied Scientist – Legal Tech
Thomson Reuters
AWSAzureCloudPythonPyTorchTensorflow
Applied Scientist, Shopping AI
Zillow
full-time
Posted on:
Location Type: Remote
Location: Remote • California, Colorado, Connecticut, District of Columbia, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Nevada, New Jersey, New York, Rhode Island, Vermont, Washington • 🇺🇸 United States
Visit company websiteSalary
💰 $134,000 - $214,000 per year
Job Level
JuniorMid-Level
Tech Stack
AirflowPythonPyTorchScikit-LearnSparkTensorflow
About the role
- Research, design, and prototype new machine learning models that will power core product features on the Zillow app, website, and email/push notifications
- Contribute to the next generation of our home ranking and recommendation systems by developing and testing novel modeling approaches
- Own the full lifecycle of your models, from offline experimentation and prototyping with massive datasets to online deployment, A/B testing, and performance monitoring
- Pioneer the application of cutting-edge deep learning and large language models (LLMs) to improve our home shopping experience
- Design and validate new AI approaches that optimize how we display and when we recommend homes, ensuring we connect shoppers with the right content on the right properties at the right time
- Collaborate in a cross-functional group of engineers, applied scientists, product managers, and designers to define, execute, and iterate on team projects
- Work closely with product and design and apply the latest advancements in AI to solve unique, large-scale challenges
Requirements
- A Master's degree in Computer Science, Artificial Intelligence, or a related field
- 2+ years of experience in an applied science, data science, or research role working on search, personalized ranking, recommender systems, or a related field
- Demonstrated experience designing, training, and analyzing machine learning models to solve business problems
- Strong programming skills in a high-level language such as Python for data analysis and modeling
- Familiarity with common machine learning libraries like PyTorch, TensorFlow, Catboost, scikit-learn and huggingface
- Experience with large scale distributed data processing systems such as Hive, Spark, Airflow, or Databricks
- Experience owning the full lifecycle of customer facing machine learning models, from offline experimentation and prototyping to online deployment, A/B testing, and performance monitoring
- Experience with the scientific lifecycle, from formulating a hypothesis and designing experiments to analyzing results and communicating findings
- U.S. employees may live in any of the 50 United States (with limited exceptions)
Benefits
- Comprehensive medical, dental, vision, life, and disability coverages
- Parental leave
- Family benefits
- Retirement contributions
- Paid time off
- Eligible for equity awards based on factors such as experience, performance and location
- Flexible work arrangements / Remote work (Cloud HQ distributed-first model)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningdeep learninglarge language modelsdata analysismodelingdesigning machine learning modelstraining machine learning modelsanalyzing machine learning modelsA/B testingperformance monitoring
Soft skills
collaborationcommunicationproblem-solvingcross-functional teamworkiteration
Certifications
Master's degree in Computer ScienceMaster's degree in Artificial Intelligence
