Senior Data Scientist

About Ascent

Ascent Developer Solutions is a leading private lending platform, serving real estate developers nationwide in the acquisition, renovation, and construction of residential real estate. Founded by a leadership team with a deep understanding and personal experience in virtually every facet of real estate development, Ascent is uniquely positioned to create custom, innovative lending solutions for a variety of real estate development business strategies.

ROLE SUMMARY

The Data Scientist is a major contributor in driving our company's innovation and data-driven decision-making. By harnessing advanced analytics, machine learning, and big data technologies, this role directly impacts strategic business outcomes, revealing actionable insights and predicting trends that shape the future of our operations. Embedded at the intersection of data and strategy, the Data Scientist empowers the organization to navigate complex challenges, optimize performance, and unlock new growth opportunities.

ESSENTIAL DUTIES

Data and analysis

• Analyze public records and other real estate data using NLP and machine learning techniques to identify patterns and cluster entities.
• Develop methods for evaluating and selecting large language models (LLMs) for deployment.
• Build predictive models to identify potential borrowers, likelihood of default, and quality/valuations of properties for lending activities.
• Identify new business opportunities through tracking competitor trends and keeping management aware of developer lending market trends and insights.
• Assist in fostering a culture of test & learn within the company.

Leadership

• Serve as analytics consultant to a broad variety of line-of-business teams.
• Partner with technology teams on product changes and impacts on data/performance.
• Mentor junior analysts on various data science techniques.

QUALIFICATIONS

• Bachelor’s degree in quantitative field.
• 5-7 years of experience in analytical or consulting roles.
• Strong data science skills with AI/ML related Python libraries such as PyTorch, TensorFlow, and Keras. Conceptual knowledge of LLM’s.
• Strong knowledge of statistics, hypothesis testing, and setting up experiments.
• Must have deployed several models to production.
• Exposure to data engineering skills.
• Strong communication and partnership skills, effective cross-department collaboration skills.
• Self-starter who can work under limited supervision.
• Mentoring skills to help develop junior analysts. </span&