Senior Data Scientist

Guild Mortgage Company, closing loans and opening doors since 1960. As a mortgage banking firm we are dedicated to serving the home owner/buyer. Our goal is to provide affordable home financing for our customers, utilizing the best terms available while providing a level of professionalism and service unsurpassed in the lending industry. 

Position Summary

The Senior Data Scientist is a key technical position and plays an important role in the organization by leading and performing number of activities related to the company’s Information Technology functions. The Sr. Data Scientist is responsible for leading the development and deployment of innovative and impactful data products and services that solve various business problems and create value for the company and its customers. The role requires a strong background in machine learning, statistics, programming, and data engineering, as well as excellent communication and collaboration skills. The Sr. Data Scientist works closely with other data scientists, engineers, product managers, and stakeholders to understand the business needs, define the data requirements, design and implement the data pipelines and workflows, apply and evaluate the machine learning models, and deliver and communicate the data analysis results and findings. The Sr. Data Scientist also mentors and coaches’ junior data scientists and engineers and stays updated with the latest research and trends in data science and related fields.

Compensation 

This role is an exempt position with a Targeted Salary Range of $124,000 to $170,000 annually.

Compensation at Guild is influenced by a wide array of factors including but not limited to local and federal minimum wage requirements, education, level of experience, and applicant’s geographical location.

Essential Functions

• Lead the development and deployment of sophisticated analytics models to predict, quantify, and interpret complex data related to mortgage lending. Utilize machine learning, statistical analysis, and other advanced techniques to improve decision-making processes, risk assessment, and customer segmentation.
• Work closely with business units to identify opportunities for leveraging company data to drive business solutions. Innovate and implement new modeling techniques and algorithms for predictive analytics and data mining Act as a thought leader, staying abreast of the latest industry trends and technologies in data science.
• Applying advanced machine learning techniques and algorithms to analyze large and complex data sets, such as supervised and unsupervised learning, deep learning, natural language processing, computer vision, recommender systems, anomaly detection, etc.
• Ensure the accuracy and integrity of data used for analysis. Implement data collection systems and other strategies that optimize statistical efficiency and data quality. Collaborate with data engineering teams to improve data collection, storage, processing, and security practices.
• Partner with IT, software development, and business teams to translate business needs into technical specifications. Design and build data-driven products and services that enhance the customer experience and contribute to the bottom Facilitate the integration of analytics and machine learning capabilities into the company’s operations and decision-making processes.
• Develop and present clear, comprehensive reports and visualizations for both technical and non-technical audiences. Communicate complex analytical results and insights in a manner that is easily understandable, facilitating informed decision-making across the company.
• Provide guidance and mentorship to junior data scientists and Lead project teams, ensuring the timely and successful completion of projects. Foster a culture of innovation, continuous learning, and collaboration within the team.
• Identify, track, and monitor trends and avoidable technology-related errors; work across functions to develop complex solutions, improvements, and stop-gaps.
• Focus on the continual improvement of policies, procedures, and processes falling under the scope of authority.
• Use expertise to resolve high level issues that cannot be solved by teammates.
• Stay abreast of latest technology trends and participate in high-level decisions impacting the direction of the Information Technology function.
• Partner with the DevOps team to setup scalable MLOps pipelines.
• Perform other duties as assigned.

Qualifications

• Bachelor’s degree in Statistics, Computer Science, Data Science, or related quantitative field is required.
• Master's Degree directly related to the position or equivalent, preferred.
• Minimum five years' ex