Senior Data Scientist: Risk & Real Estate Analytics Hybrid

Harnham; Tempe (AZ); Hybrid; USD 140,000 - 150,000; Full time

Job summary

Harnham is seeking a Lead Data Scientist to build predictive models that enhance financial decision-making and risk assessment for a national residential real estate organization. You will lead projects end-to-end within a small analytics team and present recommendations to senior executives.

The role requires regulatory experience defending models during external audits, strong Python/SQL skills, and the ability to translate findings into measurable business impact.

Qualifications

• Eight or more years of experience in data science, predictive analytics, quantitative analysis, or advanced risk modeling.
• Financial or risk modeling experience within a regulated industry.
• Direct experience supporting external model audits and defending model methodology and results.
• Advanced Python and SQL proficiency, including at least three years of experience developing models in Python and writing complex SQL queries.
• Experience with gradient boosting models, including XGBoost or CatBoost.
• Strong mathematical and statistical knowledge, including probability, sampling, predictive modeling, and model validation.
• Experience working with financial or credit datasets and translating findings into measurable business outcomes.
• Demonstrated ability to independently deliver projects from initial problem definition through implementation.
• Strong presentation skills, including experience communicating technical findings to executive audiences.
• A bachelor’s degree in mathematics, statistics, economics, computer science, quantitative engineering, or a related discipline with substantial mathematical and statistical coursework.

Responsibilities

• Own analytical projects from stakeholder intake and scoping through data preparation, model development, validation, implementation, and monitoring.
• Develop models supporting payment behavior, collectability, resident renewals, renovation costs, and repair decisions.
• Apply gradient boosting, regression, segmentation, and other statistical and machine learning methods to financial, credit, and operational datasets.
• Gather, reconcile, clean, and validate data from internal and external sources.
• Evaluate model assumptions, conduct backtesting, and document methodologies, limitations, and results.
• Defend model design, assumptions, and validation approaches during external audits.
• Translate analytical findings into financial impact, including cost savings, revenue opportunities, and changes in risk exposure.
• Present recommendations and business cases to senior leaders and executive stakeholders.
• Partner with business teams to implement solutions and measure ongoing performance.
• Mentor junior colleagues on analytical methods, project structure, and model development.

Skills

Python

SQL

Gradient Boosting

Model Validation

Executive Communication

Problem Solving

Education

Bachelor in Mathematics/Statistics/CS

Tools

Snowflake

AWS S3

Job description

Harnham is seeking a Lead Data Scientist to build predictive models that enhance financial decision-making and risk assessment for a national residential real estate organization. You will lead projects end-to-end within a small analytics team and present recommendations to senior executives.

The role requires regulatory experience defending models during external audits, strong Python/SQL skills, and the ability to translate findings into measurable business impact.