Lead Data Scientist

Imagine joining an organization where data is not just used to report on the business, but to actively shape its future. This high-growth, technology-driven company manages a large national portfolio of residential assets and relies heavily on advanced analytics to drive smarter decisions, improve customer experiences, optimize operations, and create measurable business value. Here, data scientists are viewed as strategic business partners, giving you a seat at the table with senior executives while providing the autonomy to solve meaningful, business-critical problems. This is an ideal role for an experienced Data Scientist who wants more than model development. If you're equally comfortable building machine learning solutions and presenting recommendations to executive leadership, this role offers the visibility, ownership, and impact that define a truly exceptional career opportunity. Your work will directly influence revenue, customer experience, operational efficiency, and strategic decision-making across the organization. Collaborate closely with Directors, Vice Presidents, and C-suite executives on high-priority initiatives that drive business performance. From identifying opportunities to building predictive models and implementing recommendations, you'll have meaningful ownership and autonomy. The challenges are complex, the data is rich, and the impact is real. Title: Lead Data Scientist Lead complex analytics initiatives from problem definition through implementation and measurement. Develop predictive models and machine learning solutions using large, complex datasets. Create data-driven solutions related to customer retention, risk assessment, operational forecasting, and cost optimization. Apply advanced analytical methods including supervised and unsupervised machine learning, regression analysis, forecasting, clustering, and classification techniques. Gather, clean, validate, and integrate data from multiple internal and external sources. Design dashboards, presentations, and analytical storytelling materials that influence decision-making. Identify process improvement opportunities that reduce risk and improve operational performance. Mentor and develop junior data scientists while helping elevate analytical best practices across the team. Collaborate cross-functionally with operations, finance, technology, and executive leadership teams. 10+ years of experience in Data Science, Predictive Analytics, Advanced Analytics, Quantitative Research, Risk Modeling, or a related discipline. ~ Bachelor's degree in Statistics, Mathematics, Engineering, Economics, Computer Science, or another quantitative field. ~3+ years of hands-on experience developing machine learning models using Python. ~ Advanced SQL skills with experience querying and optimizing large datasets. ~ Strong foundation in statistics, predictive modeling, probability, sampling techniques, and experimental design. ~ Strong project management and prioritization skills with the ability to manage multiple initiatives simultaneously. ~ Master's degree in a quantitative field. Experience with Snowflake and modern cloud-based data platforms. Experience with AWS environments, including S3 and related services. Background in risk analytics, portfolio management, credit scoring, or predictive risk modeling. Familiarity with model risk management frameworks such as SR 11-7. Experience leveraging algorithms such as XGBoost, CatBoost, Random Forest, Decision Trees, KNN, clustering methods, regression, and time-series forecasting.