Data Scientist, Analyst

About Cerberus

Founded in 1992, Cerberus is a global leader in alternative investing with approximately $70 billion in assets across complementary credit, private equity, and real estate strategies. We invest across the capital structure where our integrated investment platforms and proprietary operating capabilities create an edge to improve performance and drive long-term value. Our tenured teams have experience working collaboratively across asset classes, sectors, and geographies to seek strong risk-adjusted returns for our investors. For more information about our people and platforms, visit us at www.cerberus.com .

The Cerberus Asset Backed Opportunities (“CABO”) investment platform was established in 2008 to capitalize on distress in the residential mortgage sector following the Global Financial Crisis. Over the past decade, the CABO platform has continued to build upon its expertise in residential debt and has evolved to earn recognition as an innovator and market leader in securitizing performing residential loans and investing in SFR and other consumer credit and asset-based finance. The CABO platform currently manages over $20 billion and leverages three proprietary operating platforms (an asset manager, property manager, and originator) to execute its investment strategies.

Job Purpose:

Our Asset Backed Opportunities strategy focuses on generating attractive risk-adjusted returns through a combination of capital appreciation and current income, investing across mortgages, consumer credit, structured products, and real asset-backed platforms.

Within this broader strategy, our data and analytics capabilities play a central role in driving investment decisions, pricing, and portfolio performance. Over time, the business has evolved from identifying dislocation-driven opportunities to building scaled, data-enabled platforms that operate across the asset-backed landscape.

As an Analyst, Data Scientist, you will be embedded within the investment team, partnering closely with investors and operators to apply data-driven insights across the lifecycle of an investment—from underwriting and pricing to portfolio monitoring and optimization. You will contribute to the development of predictive models, analytics tools, and scalable frameworks that directly inform decision-making across the platform. This role offers the opportunity to work in a highly collaborative, fast-paced environment, tackling complex, real-world investment challenges and translating data into actionable insights that drive outcomes.

Responsibilities/Deliverables:

• Lead analytical workstreams related to rental pricing, lease renewal, economic trends to identify key metrics influencing rental pricing.
• Design, develop and implement predictive models using Python for forecasting market trends, pricing strategies, and lease renewal behavior.
• Build regression models using SQL and Python to predict optimal rental pricing.
• Conduct correlation analysis to understand relationships between rent prices and market factors.
• Evaluate market rent in various regions to inform lease renewal strategies.
• Query census data and other demographic sources to understand income levels, education, age groups, and family sizes in your target areas.
• Join internal property data with external rental comparable databases or APIs offering rental comparable (e.g., Zillow, Rentometer) based on location, property type, size and amenities
• Standardize data formats, handle missing values, and identify outliers.
• Create dashboards and visualizations in Power BI to communicate insights to key stakeholders effectively.
• Collaborate with cross-functional teams to solve business problems related to property acquisition, maintenance, and optimization.
• Embrace continuous learning and thrive in an environment with limited structured guidance.
• Comfortably learn about the real estate business on the job and adapt to new challenges.
• Mentor and support junior team members by sharing best practices, analytical approaches, and domain knowledge

Key Requirements:

• 0-2 years relevant experience (internship experience a plus) in data analytics, computer science, or information systems.
• Proficient in Python and SQL.
• Familiarity with object-oriented programming languages (Java, C#, C++, etc.) and data visualization tools (PowerBI, Tableau)
• Strong analytical and problem-solving skills with familiarity in predictive analytics techniques.
• Commercial mindset with exceptional communication skills to translate complex data insights for both technical and non-technical audiences.
• Proactive, positive, and collaborative team player with the ability to thrive in a fast-paced environment

The base salary for this position is expected to be between $90,000 and $100,000. The base salary offered to the chosen candidate will be commensurate with a candidate’s relevant experience and other qualifications for the position, as determined by the Company in its sole discretion. In addition to base salary, this position is eligible for an annual discretionary bonus and a robust benefits package.