Data Science Sr Engineer - US Remote

Anywhere Real Estate10 months ago
San Diego, CA, United States
Remote
Full-time
Junior Level (1-3 years)

Job Description

Position Overview

Work back from the business problems to be solved by collecting proper data to perform statistical analysis, selecting the appropriate machine learning and/or deep learning modeling approaches, and eventually rolling out ML models into a production environment to perfect business decisions. Meanwhile, coach junior associates during project collaborations.

At Anywhere Real Estate Inc., a leader in real estate services featuring renowned brands like Better Homes and Gardens® Real Estate, Century 21®, Coldwell Banker®, and others, we empower everyone's next move with our award-winning culture and people-first approach. Recognized as an employer of choice by Great Place to Work, Forbes World's Best Employers, Newsweek, and Ethisphere, we relentlessly pursue innovation and outstanding results.

Key Responsibilities

  • Understand business needs and explore appropriate data sources; be curious and proactive in understanding and leveraging data.
  • Perform data aggregation and feature engineering; write Python code to create visualizations, build, validate, and implement models.
  • Collaborate effectively with other data scientists and engineers.
  • Embrace innovative ideas and alternative approaches to solving problems.
  • Clearly communicate and present results to non-technical partners.

Required Qualifications

  • Master's degree (or higher) in Statistics, Data Science, Mathematics, Economics, or a related analytical discipline. (Ph.D. degree holders may omit the experience requirement.)
  • At least one year of experience in building end-to-end models in Python or a similar language.
  • Proficiency in SQL and Python programming (e.g., pandas, numpy, scipy, scikit-learn).
  • In-depth understanding of statistical methods and machine learning algorithms, with exposure to deep learning.
  • Expertise in techniques such as Linear Regression, GLM, GBM, Random Forest, XGboost, and segmentation; familiarity with Large Language Models and Neural Networks is a plus.
  • Strong communication skills and the ability to learn and independently take on new tasks.

Required Skills

Linear Regression
Random Forest
numpy
deep learning
XGboost
pandas
statistical analysis
Python
feature engineering
scipy
GLM
GBM
mentorship
scikit-learn
SQL
effective communication
data visualization
segmentation techniques
machine learning
data aggregation