Senior Data Scientist

About Ping Identity: At Ping Identity, we believe in making digital experiences both secure and seamless for all users, without compromise. We call this digital freedom. And it's not just something we provide our customers. It's something that inspires our company. People don't come here to join a culture that's built on digital freedom. They come to cultivate it. Our intelligent, cloud identity platform lets people shop, work, bank, and interact wherever and however they want. Without friction. Without fear. While protecting digital identities is at the core of our technology, protecting individual identities is at the core of our culture. We champion every identity. One of our core values, Respect Individuality, reminds us to celebrate differences so you are empowered to bring your authentic self to work. We're headquartered in Denver, Colorado and we have offices and employees around the globe. We serve the largest, most demanding enterprises worldwide, including more than half of the Fortune 100. At Ping Identity, we're changing the way people and businesses think about cybersecurity, digital experiences, and identity and access management. Summary We are looking for a Data Scientist with a strong focus on Data Modeling to join our Customer Experience (CX) BI and Analytics team, that supports Customer Success, Professional Services, Customer Support, and Renewals. Data Modeling and Analytics is the core responsibility of this role. You will design, build, and continuously improve data models including time series forecasting, regression models, capacity planning, and quota/target forecasting that enable proactive decision-making across CX functions. This role is ideal for early-career professionals aspiring to build deep expertise in applied analytics while solving real business problems, working on operational data. Key Responsibilities Data Modeling and Forecasting Develop, maintain, and enhance data models for CX use cases Support ticket inflow and backlog forecasting Capacity and staffing planning for Support and Professional Services Renewal, churn, and retention forecasting Utilization and delivery forecasting for Professional Services Apply time series techniques, regression analysis, and statistical modeling. Perform model validation, back-testing, and error analysis; continuously refine models based on business feedback. Analytical Data Preparation Use SQL and Python to extract, clean, and transform data required for data models. Perform feature engineering and exploratory data analysis to identify drivers of CX outcomes. Ensure datasets used for modeling are accurate, consistent, and well-documented. Business Insight Communication Use Excel/Google Sheets for model validation, scenario analysis, and what-if simulations. Build Tableau dashboards to visualize forecasts, trends, and model outputs. Translate data insights into clear, actionable recommendations for the business. Stakeholder Collaboration Partner closely with teams across CS, PS, GS, and Renewals to understand planning/forecasting needs. Explain modeling assumptions, limitations, and insights in business-friendly language. Support CX planning cycles (capacity planning, renewal forecasting, operational reviews). ML Ops : Build and maintain automated CI/CD pipelines for machine learning Implement systems to track model drift and data quality in production Optimize model latency and throughput for high-scale applications AI Implementation : Build and maintain AI based Predictive solutions Skills Qualifications 5–8 years of experience in BI or Data Analytics roles with a solid understanding of statistics and analytical problem-solving. Strong proficiency in Python for data modeling and data analysis, and Strong SQL skills for data extraction and transformation, preferably Databricks. Proficiency in Excel for analysis, validation, scenario modeling and Tableau dashboards building. Hands-on experience with time series ... (truncated, view full listing at source)