Senior Data Scientist

Role Overview

• 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.
• Apply 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 [{not fully visible in given text}].
• 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.

Requirements

• 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' experience in Data Science related role(s) and two of those years spent in a senior level role(s) required.
• A combination of education and related experience may be considered in lieu of experience requirements.
• Expertise in statistical software (e.g., R, SAS), programming languages (e.g., Python, SQL), and big data technologies (e.g., Hadoop, Spark).
• Strong experience with machine learning libraries (e.g., scikit-learn, TensorFlow) and data visualization tools (e.g., Tableau, PowerBI).
• Proven experience with data lake and warehouse best practices and leading products in the marketplace.
• Experience collecting structured, semi-structured and unstructured data in various popular formats and sourced from internal core systems as well as 3rd partner providers such as Google Analytics, Facebook Insights, Zillow, CoreLogic, MLS Data, Public Records, and Property Data.
• Exceptional analytical and quantitative problem-solving skills.
• Ability to work with complex datasets and extract meaningful data.
• Strong understanding of statistical analysis, predictive modeling, and machine learning algorithms.
• Demonstrated ability to lead and manage projects and strong mentoring and coaching skills to nurture talent within the team.
• Ability to inspire and drive innovation.
• Strong strategic thinking and planning.
• Ability to align data science activities with business objectives.
• Proven capability to work under pressure and adapt to changing business environments.
• Ability to prioritize multiple tasks in a deadline-driven environment, strong sense of urgency and responsiveness.
• Strong detail orientation and highly organized with proven ability to lead effectively and drive results in a matrixed management environment.
• Ability to think critically, including the ability to evaluate facts and data to draw conclusions, determine the downstream impact of decisions and associated risks.
• Self-starter with the demonstrated ability to learn/adapt to new technologies and techniques.
• Excellent verbal and written communication skills required.
• Highly organized and detail-oriented; ability to work in a fast-paced, metrics-driven environment required.
• Proficiency in Microsoft Office Suite, Word, Excel, Wiki, collaborative cloud-based programs, and third-party software applications required.
• Commitment to company values.

Tech Stack

• Cloud
• Hadoop
• Python
• Scikit-Learn
• Spark
• SQL
• Tableau
• Tensorflow

Benefits

• Medical
• Dental
• Vision
• Life insurance
• AD&D
• LTD
• 401(k) with employer match