Data Scientist

Since opening our first self-storage facility in 1972, Public Storage has grown to become the largest owner and operator of self-storage facilities in the world. With thousands of locations across the U.S. and Europe, and more than 170 million net rentable square feet of real estate, we're also one of the largest landlords.

We've been recognized as A Great Place to Work by the Great Place to Work Institute. And, our employees have also voted us as having Best Career Growth, ranked us in the Top 5% for Work Culture, and in the Top 10% for Diversity and Inclusion.

We're a member of the S&P 500 and FT Global 500. Our common and preferred stocks trade on the New York Stock Exchange.

Public Storage is the nation’s leading self-storage provider, recognized for its iconic orange doors and commitment to delivering simple, reliable solutions to millions of customers across the country. We are expanding our creative team to enhance our consistent and engaging visual brand presence.

Responsibilities

• Exceptional verbal and written skills to convey ideas, problems and solutions
• Establish trust and confidence as the data scientist, up, across, and down the organization
• Design, build, and deploy ML models across structured and unstructured data
• Translate ambiguous business problems into well-scoped analytical solutions with clear trade-offs documented
• Write production-grade Python and SQL; contribute to shared codebases with reproducibility and refactorability in mind
• Collaborate with data engineering on pipeline architecture, feature stores, and model deployment patterns
• Leverage LLMs and modern AI tooling where appropriate, sound judgment on when not to
• Mentor analysts and junior data scientists through code review, whiteboarding, and hands-on pairing
• Own model documentation, versioning, and knowledge artifacts (Confluence, GitHub)
• Monitor deployed models for drift and degradation; refresh proactively, not reactively
  
  

Required:

• Bachelor's/Master's in a STEM field (statistics, economics, CS, engineering, applied math, or similar)
• Expert in SQL and Python in real-world

Preferred:

• Ph.D. in a quantitative field a plus, equivalent experience considered: 5+ years in a production data science role
• Alternative to education, 6+ years of experience as contributor/leader
• Demonstrated track record shipping models that drove measurable business outcomes

Skills & Abilities

• Strong verbal communication skills: ability to effectively communicate cross-functionally

• Expert-level SQL and Python in production settings
• Strong applied statistics — comfortable in frequentist and Bayesian frameworks
• Experience with the modern ML stack: scikit-learn, XGBoost, PyTorch or equivalent; experiment tracking (MLflow, W&B, or similar)
• MLOps fundamentals: versioning, model registries, scheduled retraining, monitoring
• Git-based workflows (GitHub or GitLab) with code review habits
• Familiarity with dbt or orchestration tools (Airflow, Prefect, etc.)
• Exposure to web behavioral data and customer lifecycle modeling (churn, propensity, LTV)
  
  

Workplace

• One of our values pillars is to work as OneTeam and we believe that there is no replacement for in-person collaboration but understand the value of some flexibility. Public Storage teammates are expected to work in the office five days each week with the option to take up to three flexible remote days per month.
• Comp Range: $155,000 - $170,000

Public Storage is an equal opportunity employer and embraces diversity. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other protected status. All qualified candidates are encouraged to apply.

**Sponsorship for Work Authorization is not available for this posting. Candidates must be authorized to work in the U.S. without restrictions or requiring sponsorship now or in the future. We do not provide training plans or support for F-1 OPT, STEM OPT extensions, or future visa sponsorship.**