Mr. Cooper Group-posted 8 months ago
Full-time • Senior
Remote • Lewisville, TX
Credit Intermediation and Related Activities

We are Xome, a real estate services company headquartered in the Dallas, Texas area. As a subsidiary of Mr. Cooper Group, we employ over 1,200 team members nationwide. The nation's largest financial services companies look to us for integrated and scalable business solutions that help simplify the mortgage and real estate process. At the heart of everything we do is our purpose: To keep the dream of home ownership alive. If that sounds like a big, lofty goal, that's because it really is. And we can't do it alone. Our entire team is focused on helping create a stable and healthy housing industry. And, making sure the process of buying/selling a home doesn't undermine the excitement of home ownership. That's why we battle every day against the mediocrity of the status quo to simplify the complex world of mortgage servicing, lending and banking. We see ourselves as the experts who make doing business easier. While others bring complexity and a lack of transparency, we offer simplicity, trust, and visibility across the entire property lifecycle. And we deliver radical customer service.

  • Write efficient and robust queries to extract, modify and prepare the data for pre-processing from different structured, semi-structured, and unstructured datasets using SQL Servers, Databricks, Azure Data Factory and other cloud vendors.
  • Train/Re-train a variety of Genetic Algorithm, Neural Network, Linear Regression, Gradient Boosting and other Supervised and Unsupervised ML models, using frameworks such as Tensorflow, PyTorch, Keras, and Sci-Kit Learn by building scalable programs and applications, debugging and deploying them.
  • Conduct multivariate/univariate statistical analysis and feature distribution analysis on different domain specific datasets, to generate meaningful insights before being used in the ML models.
  • Design, develop and implement MLOPs architecture, CI/CD pipelines, using MLFlow, Docker, asset bundles etc.
  • Conduct literature review in the AVM/Real Estate domain and ML/AI domain of new publications, industry improvements, which contribute to the model/solution design process.
  • Design, develop and implement Natural Language Processing (NLP) pipelines, that involve elements such as NER etc.
  • Design, develop and implement Large Language Models (LLMs) and Gen AI solutions.
  • Review ML models' design, implementation, domain applicability of team members projects, and mentor junior data scientists on different ML models and workflows.
  • Collaborate with Data Architecture, Data Engineering, Product, Marketing and other teams on strategizing ML/AI initiatives.
  • Bachelor's degree in Computer Science, Data Science or another related field of study and five (5) years of experience as a Machine Learning Engineer, Software Developer, or a related occupation.
  • Experience in ML tools like TensorFlow, PyTorch, Caffe, or Theano and have solved several real-life problems using these.
  • Proficiency and experience in NLP like text processing, information retrieval, NER.
  • Experience in NLP, Vision, Classification, Extraction, Regression, Clustering, and Forecasting.
  • Building deep learning models with TensorFlow/Keras or PyTorch.
  • Proficiency in Python and libraries for machine learning (such as scikit-learn, NumPy, Pandas, OpenCV).
  • Experience in data visualization, manipulation, versioning of big datasets.
  • Experience in feature engineering.
  • Experience in building the MLOps pipelines (using DataBricks, DVC, Kubeflow, Airflow, or Vertex AI, etc.).
  • Experience in designing, building, and managing automation pipelines to operationalize the ML platform that should automate building Docker images, model training, and model deployment.
  • Familiarity with low-code and Auto ML libraries (for example, PyCaret and AutoKeras).
  • Experience with Azure technologies: Cloud Machine Learning, App Engine, Pub/Sub Streaming, Cloud Functions, Cloud Data Store and SQL.
  • Experience in cloud-native development (Docker, Kubernetes, and DevOps) and the ability to select hardware to run an ML model within the expected latency.
  • Experience with AI products such as Azure Machine Learning, Amazon SageMaker, DataBricks, AutoML, etc.
  • Ability to write code in programming languages such as Python or Java.
  • Experience in designing, building and working with RESTful Web Services in JSON and XML formats.
  • Familiarity with version control tools such as Git.
  • Theoretical and practical knowledge of SQL / NoSQL databases with hands-on experience in at least one database system.
  • Familiarity with software development methodology such as Agile/Scrum.
  • Diversity and inclusion initiatives.
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