At CoreLogic, we are driven by a single mission—to make the property industry faster, smarter, and more people-centric. CoreLogic 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.
CoreLogic 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 CoreLogic, 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
CoreLogic is seeking a Principal, Machine Learning Scientist to contribute towards innovation and use data science and artificial intelligence methods to deliver best-in-class solutions. Our Data, Science & Analytics team works across our big data cloud platform and data supply chain, using advanced analytics, machine learning, AI, and deep learning methods to make an impact across our entire data ecosystem. The team uses emerging technologies and methods such as data fabric, machine learning, GenAI, NLP, computer vision, artificial intelligence automation, big data analytics, and cloud native application development to drive innovation, operational efficiency, and provide the data product excellence our customers have come to value and trust us for.
What You’ll Be Doing To Drive Innovation
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. Design data frameworks, develop algorithmic models and analytic capabilities based on rules engine, machine learning, mathematical modeling, pattern recognition, and data mining techniques. Leverage big data tools, geospatial methods, and programming frameworks to ensure that the data gathered from data pipelines can be applied to data science models and the model outputs are ready to scale as needed.
Job Responsibilities
- Develop and program integrated software algorithms to structure, analyze and leverage data in product and systems applications.
- Use machine learning and statistical modeling techniques to improve product/system performance, quality, data management and accuracy.
- Use current programming languages and technologies to translate algorithms and technical specifications into code. Develop data frameworks that connect diverse data elements into logical and performance optimized data pipelines.
- Work with large scale computing frameworks, data analysis systems and modeling environments.
- Create data derivation and linkage through algorithm and/or data rules.
- Create reports with data visualization 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 problems (e.g., clustering, logistic regression, deep learning, support vector machines, boosting trees, supervised and unsupervised models).
- Develop data, analytic, and data science models using Python, PySpark, Large Language Models (LLM) algorithms, and working with other big data tools such as AutoML, BigQuery(BQ), BQML, DataPrep and Jupyter Notebook.
- Build programs that control the flow of data, model processing and output generation, and integration to the rest of the analytics platform using big data tools such as AirFlow, DataFlow, and DBT.
- Perform complex data analysis on large volumes of property and spatial data and present to stakeholders.
- Lead the entire data, science & analytics development lifecycle for key initiatives (research, design, experimentation, development, deployment, monitoring, and maintenance).
- QA and analyze large amounts of data to create appropriate data sets for model building.
- Provide model deployment support.
- Prepare and maintain programs and documentation for analytic models.
- Conduct defined quantitative and qualitative research projects independently and communicate research results to internal and external stakeholders.
- Lead and provide technical leadership on data, science & analytics projects with other data scientists, ML engineers, data engineers, and data analysts.
Job Qualifications
- Master’s Degree or higher in computer science, computer applications, artificial intelligence, data science, engineering field, or equivalent work experience.
- At least 5-10 years’ directly related experience in computer applications, large scale computing frameworks, data analysis systems, machine learning techniques, data engineering, and pipeline design for real world problems.
- Deep experience and knowledge with Google Cloud Platform, Cloud Dataflow, Airflow, GKE, Pub/Sub, BigQuery, vertex AI, and Dataproc/Spark.
- Significant experience working with Python, Spark, SQL, Bash, BigQuery.
- Ability to thrive in a team environment and adapt to quickly changing priorities.
- Strong problem solving and analytical ability.
- Ability to quickly and efficiently adapt to new concepts.
- Experience working with large amounts of data, databases, and streaming in a high throughput environment. Data mining experience.
- Strong working knowledge with a variety of analytic development, statistical, and big data tools.
- Detail oriented; strong presentation skills, experienced with client interaction.
- Strong communication skills and cross-functional team experience; strong and effective communicator to partners, clients, and colleagues with the ability to explain business needs to technical personnel both verbally and in written form.
- Ability to lead small teams in technical projects and manage multiple, complex projects simultaneously.
- Expertise in formulating business problems and designing analytic approaches.
- Able to effectively present analytic insights and modeling techniques internally and externally.
- Recognized as technical expert, significant contributor, and strong leader.
- Demonstrated general business acumen; experience working in a real estate and mortgage-related data industry.
Annual Pay Range
135,900 - 200,265 USD
CoreLogic benefits information can be found here: . Qualifications, locations, and experience of the individual ultimately selected for the position may impact the final actual offered compensation, which may vary from any posted range.
CoreLogic's Diversity Commitment
CoreLogic is fully committed to employing a diverse workforce and creating an inclusive work environment that embraces everyone’s unique contributions, experiences and values. We offer an empowered work environment that encourages creativity, initiative and professional growth and provides a competitive salary and benefits package. We are better together when we support and recognize our differences.
EOE AA M/F/Veteran/Disability
CoreLogic is an Equal Opportunity/Affirmative Action employer committed to attracting and retaining the best-qualified people available, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, disability or status as a veteran of the Armed Forces, or any other basis protected by federal, state or local law. CoreLogic maintains a Drug-Free Workplace.
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