Data Scientist

Become the newest member of our exciting team at SROA Capital as we redefine self-storage

At SROA, we offer a career and opportunity to grow. We strongly believe in growing our talent and promoting within. We are proud to be honored as one of the TOP WORKPLACES of South Florida by the Sun Sentinel three years in a row.

SROA Capital is a vertically integrated private equity real estate investment firm that has evolved into a global asset manager with a successful track record of providing risk adjusted returns to its partners through its focused strategy of investing in self-storage. SROA is headquartered in West Palm Beach, FL and has invested, redeveloped, and developed self storage across the risk spectrum in major and secondary markets across the United States under the brand Storage Rentals of America and the UK under the brand Kangaroo Self Storage with approximately 900 employees globally.

The Data Scientist will apply statistical analysis, predictive modeling, machine learning, and AI-enabled analytics to trusted company data. This role will help transform data into insights, predictions, recommendations, and reusable analytics products while developing a strong understanding of SROA business operations and data assets.

This role will support use cases across revenue management, customer behavior, operations, marketing, investment analysis, and customer experience and will work with Data Intelligence leadership, analytics engineering, business intelligence, data engineering and business stakeholders. The position is designed for an early-career professional who has a strong foundation in statistics, programming, and analytical problem-solving and is eager to grow through hands-on work with real business problems.

Duties and Responsibilities

• Assist in developing, testing, and maintaining predictive models, statistical analyses, and machine learning solutions for business use cases
• Explore and analyze structured data to identify trends, relationships, anomalies, and opportunities that can improve business performance
• Partner with business stakeholders and Data Intelligence team members to understand business questions, define analytical approaches, and translate findings into actionable insights
• Prepare, clean, validate, and transform data for analysis in collaboration with analytics engineering and data engineering resources
• Build reproducible analytical workflows using SQL, Python, or similar tools and document assumptions, methods, model inputs, and results
• Evaluate model performance using appropriate statistical and machine learning techniques and communicate limitations, risks, and expected business impact
• Support experimentation, forecasting, segmentation, optimization, and other advanced analytics initiatives as assigned
• Create clear visualizations, summaries, and presentations that explain analytical findings to technical and non-technical audiences
• Contribute analytical outputs and model results to dashboards, reports, and other data products in partnership with business intelligence resources
• Follow Data Intelligence standards for metric consistency, data quality, governance, documentation, version control, and analytical reproducibility
• Research emerging data science, machine learning, and AI techniques and help evaluate practical applications within SROA
• Contribute to a collaborative Data Intelligence operating model focused on trusted data, reusable assets, consistent analytics, and measurable business value
• Other projects as assigned

Required:

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative field, or equivalent practical experience
• 0-2 years of professional, internship, academic, or project experience applying data science, statistical analysis, machine learning, or advanced analytics techniques
• Working knowledge of Python and common data analysis libraries such as pandas, NumPy, scikit-learn, or similar tools
• Working knowledge of SQL and the ability to query, join, aggregate, and validate data from relational data sources
• Foundational understanding of statistics, probability, regression, classification, model evaluation, and experimental or analytical design
• Ability to clean, explore, analyze, and visualize data and explain findings in a clear, business-o