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Ascent Developer Solutions

Machine Learning Engineer

Reposted Yesterday
In-Office
Encino, CA, USA
130K-150K Annually
Senior level
In-Office
Encino, CA, USA
130K-150K Annually
Senior level
Design and deploy ML and NLP models (including LLM evaluation) to predict borrower risk and property valuations, advise business teams, mentor junior analysts, and foster data-driven experimentation.
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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 Machine Learning Engineer 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. 

WORK ENVIRONMENT 

  • This role works on-site from Ascent's Encino office 2 days per week 

THE PAY 

Salary range is $130,000-$150,000 per year, with a discretionary bonus of 20% per year. 

Our Benefits

We offer a comprehensive benefits package designed to support your health, well-being, and work-life balance. Our benefits include four health plans, two dental plans, health savings account with employer contribution, flexible spending accounts, vision coverage, a 401(k) plan, and other optional benefits from which to choose.

Our Pledge

We pledge to be fair and considerate in hiring and promoting individuals, ensuring everyone can contribute their fullest potential regardless of background, identity, or personal circumstances. By promoting equal opportunity, we not only enhance our workplace but also contribute to a more just and equitable society. At Ascent, we stand united in building a community where everyone is empowered to succeed. Thank you for joining us on our journey towards a more inclusive future.

HQ

Ascent Developer Solutions El Encino, California, USA Office

El Encino, CA, United States

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