Red Hat-posted 3 months ago
$138,200 - $187,000/Yr
Full-time • Senior
5,001-10,000 employees

This position is a hybrid role requiring employees to work from our headquarters location in Seattle, WA every Tuesday and Wednesday, and remote all other days. Hybrid from Seattle is the preferred location but this role is open to fully remote candidates. Redfin is revolutionizing the $75 billion real estate industry. We use data, beautiful software, and innovative design to put customers first at every step in the home-buying and selling process. Get ready to dive headfirst into our award-winning website and mobile apps, solving complex business problems in a highly visible, customer-centric way. If you value doing great work in a collaborative environment, join our team! The Applied Machine Learning group at Redfin works towards redefining real estate in the customer’s favor using machine learning. We work on foundational problems in the real estate space including recommendations and price estimation. The Brokerage Recommendations product alone drives 27% of all traffic to Redfin platforms. We have real estate data at a national level and work across various domains in machine learning using large-scale multi-modal property data. Our team also owns and maintains end-to-end production-grade large-scale machine learning infrastructure and systems serving hundreds of millions of consumers. As a Senior Data Science Engineer for the Applied Machine Learning Team, your job is to leverage advanced analytical techniques and statistical modeling to extract meaningful insights from our vast datasets, driving the development and improvement of our machine learning solutions.

  • Design and implement advanced statistical models and machine learning algorithms to solve complex real estate problems.
  • Perform comprehensive Exploratory Data Analysis (EDA) to understand data structure, distributions, and anomalies.
  • Apply feature engineering techniques to optimize model performance.
  • Co-create the next generation of data-driven insights for automated valuation and recommender systems.
  • Identify and implement improvements to ML models that power production-scale customer-facing experiences.
  • Assist other engineers and stakeholders in understanding and utilizing data science methodologies and findings.
  • Build data products and analytical tools that drive critical metrics and impact revenue growth.
  • 5+ years of experience in data science, statistical modeling, and software engineering.
  • Experience with open-source data science tools.
  • Required Skills: Python (Scikit-learn, PyTorch, Tensorflow/Keras, NumPy, Pandas, XGBoost), SQL, A/B testing, statistical modeling, data visualization.
  • Experience developing large-scale data applications backed by relational and non-relational databases.
  • Experience with Recommender Systems.
  • Preferred Skills: Spark, Apache Airflow, AWS (S3, DynamoDB, Lambda, Kinesis, SageMaker).
  • Competitive compensation packages with a salary, bonuses, and restricted stock grants.
  • Generous benefits, including paid vacation, medical, dental, and vision insurance, and fully paid family leave.
  • Opportunities for continued professional development and growth.
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service