Data Scientist, Risk

Kiavi is one of the nation’s largest private lenders to residential real estate investors (REIs). We harness the power of data & technology to offer our customers a simpler, more reliable, and faster way to access the capital they need to scale their businesses. 

Formerly known as LendingHome, we’re committed to helping REIs revitalize the approximately $25 trillion worth of aged U.S. housing stock to provide move-in ready homes and rental housing for millions of Americans across the country.

Combining our technology and industry expertise, Kiavi has grown to a team of over 400 and has won many awards over the years including Forbes Fintech 50, Finovate Awards, Best Digital Mortgage Platform, Fast Company’s Most Innovative Companies, and many more. 

• Loans Funded: $18+ billion in loans funded 
• Homes financed: 71,000+ projects funded for our customers across the country
• Geography: 31 states + D.C. where we lend to REIs so they can revitalize neighborhoods
• Employees: Over 400 employees with competitive benefits and perks

This position can be based remotely in any of our approved hiring regions. Our hybrid distributed workforce philosophy allows us to find the best talent in the country and build diverse teams, while allowing our colleagues to work from the location that works best for them. 

At this time, we are not approved to hire in the following regions for this role: Alabama, Alaska, Arkansas, California, Connecticut, Delaware, Idaho, Indiana, Iowa, Louisiana, Massachusetts, Mississippi, Montana, New Hampshire, New Jersey, New Mexico, North Dakota, Oklahoma, South Dakota, Vermont, Wyoming. As well as: NYC Metro Area, Seattle Metro, Washington DC Metro, Baltimore Metro, Boston Metro, Chicago Metro, Houston Metro, Denver Metro, Portland Metro. 

THE TEAM

Our Risk Analytics team is made up of 360-degree thinkers that analyze complex problems and come up with creative solutions. We love to combine advanced analytics and machine learning skills with deep domain knowledge about the business when creating solutions. You will work with some of the most fascinating data sets in the world, alongside a world-class group of product engineers, sales and marketing leaders, and business operators.

PURPOSE OF THE ROLE

Kiavi’s Risk Analytics team is seeking a talented Data Scientist to join us in our effort to reinvent real estate investment lending. You will be working with the Director of Risk Analytics to tackle fun business problems related to credit risk management, asset valuation, process optimization, and more. An ideal candidate should be able to utilize advanced data manipulation and modeling techniques to work on structured and unstructured data to solve complex business problems. You’ll also have interaction with MLOps engineers, Product Managers, and Capital Markets subject matter experts to help drive select initiatives. If you are keen on joining a dynamic company and working on intellectually challenging problems in a fast paced environment, please reach out to us.

KEY RESPONSIBILITIES:

• Develop and maintain innovative models for loan underwriting. This requires thorough statistical analysis of the underlying data and understanding of the various macroeconomic factors and risk factors that impact the credit quality of borrowers.
• Develop models for portfolio management purposes such as loss forecasting, loan modifications and collections
• Closely provide regular ongoing model performance assessments and enhance existing models
• Develop analytical tools to support other teams
• Working with the technology team, drive initiatives to enhance data capabilities and streamline infrastructure
• Work closely with engineers/data infrastructure team in designing useful data attributes
• Perform exploratory analysis and make recommendations on improving current data models, decisioning framework, etc.
• Refactor existing analytic solutions to improve scalability 

EXPERIENCE & QUALIFICATIONS: 

• Bachelor's degree in a quantitative discipline (e.g., statistics, economics, finance, physics, mathematics) and 2+ years of work experience in a modeling group at a commercial bank, investment bank, consulting firm, or fintech company
  OR
  Advanced degree (PhD or MS) in a quantitative discipline
• Statistical skills especially in model development at an account or customer level.
• Solid understanding of machine learning techniques
• Strong programming skills in R, SQL, Python
• Team player with strong interpersonal skills
• Excellent oral and written communication skills with the ability to explain technical concepts in practical terms

PREFERRED REQUIREMENTS:

• Progress towards FRM or CFA certification
• Hands on experience with loan underwriting/scoring/default/prepayment models 
• Exposure to time-to-event/survival analysis problems
• Experience in handling unstructured data
• Experience with Spark
• Experience with Monte Carlo simulation and/or Bayesian statistics

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Kiavi takes a market-based approach to pay, and pay may vary depending on your location. The expected annualized base pay range for this full-time role to be performed remotely is $136,200 - $204,400 + equity + benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries. Within the range, the successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. Your recruiter can share more about the specific base pay range for your preferred location during the hiring process. Please note that the pay range listed above reflects the base salary only, and does not include the target value of equity, or benefits.

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Benefits and Perks 

• Medical, Dental, and Vision Insurance: Kiavi offers free employee-only coverage for medical, dental, and vision plans. Dependents receive a heavily discounted premium, competitively placed in the 90th percentile for cost.
• Health Savings Account (HSA): For those enrolled in a High Deductible Health Plan (HDHP), Kiavi provides an annual employer contribution to HSAs: $500 for individual coverage and $1,000 for dependents.
• Disability and Life Insurance: Immediate access to short-term and long-term disability insurance, as well as group life and AD&D insurance, with coverage at 1x annual salary.
• Remote Work Policy: Kiavi supports working remotely for day to day activities for most roles and occasionally may ask employees to gather in person for key meetings, trainings, team building etc. For remote workers, Kiavi offers a one-time office setup reimbursement of up to $500 and a monthly $75 stipend for internet and phone expenses. For in-office workers, Kiavi offers employer contributions to commuter benefits account, either for parking or public transportation.
• Flexible Time Off: Employees are empowered to manage their own time off, with no strict limits, as long as it's approved by their manager.
• Paid Leaves: Up to 8 weeks of paid leave for medical or caregiver purposes, and 12 weeks of paid maternity/paternity leave. Short-term disability leave is also available for birthing mothers.
• 401(k) & Company Match: A 401(k) plan managed by Fidelity, with Kiavi matching 100% of contributions up to 3% of compensation or $4,000 (whichever is less). All employer contributions are immediately vested.
• Product Ownership: All employees think like an owner because all employees play a critical role in making our business great. Many roles are eligible for stock option grants.

Kiavi in the News:

• Comment start HousingWire: 2023 HW Tech100 Winner: Kiavi 
• PropTech Connect: Kiavi Closes $209M To Grow Its Funding Capacity 
• CrowdFund Insider: Kiavi Closes $158M Revolving Securitization of Residential Transition Loans 
• Mortgage Professional America: Real investors’ lender Kiavi achieves milestone  
• Inc Magazine: 2022 Best Places to Work: Kiavi  

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If you'd like to see more about what Kiavi has to offer or explore additional opportunities, visit our careers page. 

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Kiavi is an Equal Opportunity Employer
San Francisco Fair Chance Ordinance Police Code, Article 49

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Last updated on Aug 13, 2024