Data Scientist - Model Validation (Hybrid)

Data Scientist - Model Validation (Hybrid)

Enova

Chicago, IL • Hybrid

$87K - $110K/yr

Other

Medical, Dental, Vision, Retirement, PTO

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Job description

Data Scientist - Model Governance (Hybrid)

Chicago, IL

We are interested in every qualified candidate who is eligible to work in the United States. However, we are not able to sponsor visas or take over sponsorship at this time.

About the Role

As a Data Scientist, you will be one of Enova's most valuable team members. You will develop, enhance and test the company's models for use in determining the appropriate lending criteria and verification procedures. You will perform independent model validations to evaluate model fit for purpose, conceptual soundness, mathematical theory and assumptions, data/assumptions, and output reasonableness. At times, you may be asked to conduct ad hoc analysis using statistical and financial tools to recommend for risk management, marketing and operational strategies. You will demonstrate the ability to interpret and organize data, and communicate it effectively to cross functional teams to solve business problems, provide requirements and support implementation.

Responsibilities
  • Perform model validation of credit risk models
  • Prepare model validation reports and write technical documentation
  • Assist analysts in validating and preparing their models for production
  • Interact with model stakeholders and business partners to gather information about credit models and risk acceptances
  • Support model releases to ensure they are quickly and accurately put into production
  • Monitor model performance dashboards, build alerts, and escalate concerns as appropriate
  • Support and improve automated model training processes by using data manipulation, and machine learning skills
  • Use your programming skills to develop and test programs for custom tool development
Requirements
  • Experience in developing advanced credit risk models
  • 3+ years of experience in quantitative analysis in the financial services industry is preferred but not required
  • Knowledge of statistical models in risk management
  • Advanced programming skills in Python and the ability to write customized programs for meaningful data analysis
  • Experience working with relational databases, such as SQL
Compensation

The budgeted annual salary range for this position is $87,000 to $110,000. Actual annual salary will be determined based on qualifications, skills, experience, and level assessed during the hiring process and may fall outside of the range shown. Additional compensation for this role may include a bonus. All full-time employees are eligible to participate in Company benefits, described in more detail here.

Benefits & Perks
  • Our hybrid roles require in-office work Tuesday through Thursday, with remote flexibility on Mondays and Fridays. This schedule fosters collaboration, team connection, and strategic planning, enhancing communication and effectiveness to drive results.
  • Health, dental, and vision insurance including mental health benefits
  • 401(k) matching plus a roth option (U.S. Based employees only)
  • PTO & paid holidays off
  • Sabbatical program (for eligible roles)
  • Summer hours (for eligible roles)
  • Paid parental leave
  • DEI groups (B.L.A.C.K. @ Enova, HOLA @ Enova, Women @ Enova, Pride @ Enova, South Asians @ Enova, APEX @ Enova, and Parents @ Enova)
  • Employee recognition and rewards program
  • Charitable matching and a paid volunteer day…Plus so much more!
About Enova

Enova International is a leading financial technology company that provides online financial services through our AI and machine learning-powered Colossus™platform. We serve non-prime consumers and businesses alike, while offering world-class technology and services to traditional banks—in order to create accessible credit for millions.

Being a values-driven organization is at the core of Enova's success. We live our values by listening to our customers, challenging assumptions, thinking big, setting high expectations, and hiring and developing the best. Through our values and our commitment to making Enova an awesome place to work, we maintain an environment of inclusion and culture where our employees can thrive. You can learn more about Enova's values and culture here.

It is our policy to provide equal employment opportunity for all persons and not discriminate in employment decisions by placing the most qualified person in each job, without regard to any other classification protected by federal, state, or local law. California Applicants: Click here to review our California Privacy Policy for Job Applicants.




Frequently asked questions

Q: What skills or qualities help someone succeed as a Data Scientist?

A: To succeed as a Data Scientist, one must possess core technical skills such as proficiency in programming languages like Python, R, or SQL, as well as expertise in machine learning algorithms, data visualization tools like Tableau or Power BI, and statistical modeling techniques. Additionally, strong soft skills like effective communication, collaboration, and problem-solving abilities, along with traits like curiosity, adaptability, and attention to detail, are crucial for success in this role. By combining these technical and soft skills, Data Scientists can effectively extract insights from complex data, drive business decisions, and drive career growth through continuous learning and innovation.

Q: What is the career path for a Data Scientist?

A: A Data Scientist's typical career progression involves starting as a Junior Data Analyst or Data Scientist, where they develop foundational skills in data analysis, machine learning, and visualization. As they gain experience, they can move into mid-level roles such as Senior Data Scientist or Lead Data Analyst, where they take on more complex projects, mentor junior team members, and contribute to strategic decision-making. Ultimately, senior Data Scientists can transition into leadership positions like Director of Data Science or Chief Data Officer, or pursue specialized roles like Data Engineering or Artificial Intelligence Research Scientist, depending on their interests and skills.