About the role
At Cotality, we are driven by a single mission—to make the property industry faster, smarter, and more people-centric. Cotality is the trusted source for property intelligence, with unmatched precision, depth, breadth, and insights across the entire ecosystem. Our talented team of 5,000 employees globally uses our network, scale, connectivity and technology to drive the largest asset class in the world. Join us as we work toward our vision of fueling a thriving global property ecosystem and a more resilient society. Cotality is committed to cultivating a diverse and inclusive work culture that inspires innovation and bold thinking; it's a place where you can collaborate, feel valued, develop skills and directly impact the real estate economy. We know our people are our greatest asset. At Cotality, you can be yourself, lift people up and make an impact. By putting clients first and continuously innovating, we're working together to set the pace for unlocking new possibilities that better serve the property industry. Job Description: Design, develop, and deliver solutions that will enhance and add value to new and existing data assets for broad industry application and aligned with business and market
requirements. Develop algorithmic and rule-based models and analytic capabilities based on rules engine, machine learning, mathematical modeling, pattern recognition, and data mining techniques. Performs data analysis, feature engineering and model development using a variety of analytic techniques, tools, and programming languages to provide business insights and analytic products. Job Duties Create data derivation and linkage through algorithm and/or data rules. Create and select predictive features from raw data. Create model reports for stakeholder review and model documentation. Perform pattern recognition model creation and training using various types of algorithms and machine learning modeling techniques for unknown or less well-defined – an unknown problem, solve new problems (e.g., clustering, logistic regression, deep learning, support vector machines, boosting trees, supervised and unsupervised models). Develop analytics using Python, PySpark and other big data tools such as AutoML, BigQuery(BQ), BQML, DataPrep and Jupyter Notebook. Develop analytics solutions using traditional database technology such as SQL and big data technology such as Hadoop, MongoDB, Cassandra, Redis, PostgreSQL and Neo4j, NoSQL databases. Perform complex data analysis on large volumes of property and consumer data and present model performance to stakeholders. Provide data science and analytic support for the Enterprise Data Solutions Group (EDSG) and interact with other EDSG teams as well as other business units. QA and analyze large amounts of data to create appropriate data sets for model building. Prepare and maintain programs and documentation for analytic models. Conduct defined quantitative and qualitative research projects independently and communicates research results to internal and external stakeholders. Act as a consultant to EDSG’s data management and data technology teams. Lead and provide technical leadership on data science project with other data scientists, data engineers, and data analysts. Job
