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 forecasting and regression techniques.
Exposure to capacity planning, churn modeling, or operational forecasting.
Familiarity with cloud data platforms (AWS, GCP, or Azure), and Git, GitHub.

Education

Bachelor’s degree in Engineering, Computer Science, Statistics, Mathematics, or a related quantitative field.
MBA (preferred), ideally with a specialization in Analytics, Operations, Strategy, or Finance.

Life at Ping:

We believe in and facilitate a flexible, collaborative work environment. We’re growing quickly, but remain true to the innovative, can-do startup values that got us here. Most importantly, we keep hiring talented, smart, fun, and genuinely nice people because that’s who we want to succeed with every day.

Here are just a few of the things that make Ping special:

A company culture that empowers you to do your best work.
Employee Resource Groups that create a sense of belonging for everyone.
Regular company and team bonding events.
Competitive benefits and perks.
Global volunteering and community initiatives

Our Benefits:

Generous PTO & Holiday Schedule
Parental Leave
Progressive Healthcare Options
Retirement Programs
Opportunity for Education Reimbursement
Commuter Offset (Specific locations)

Ping is the collective sum of all our individual experiences, backgrounds and influences and we pride ourselves in growing and learning together. We are committed to building an inclusive and diverse environment where everyone’s individuality is respected and everyone has an Identity. In recruiting for new colleagues, we welcome the unique contributions you can bring and encourage you to be your best self.

We are an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex including sexual orientation and gender identity, national origin, disability, protected Veteran Status, or any other characteristic protected by applicable federal, state, or local law.

Senior Data Scientist

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