About eNOVA
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Industry
Advertising and public relations services
Company size
51 - 200 Employees
Headquarters location
New Providence, NJ, US
Year founded
2002
$87K - $110K/yr
Other
Medical, Dental, Vision, Retirement, PTO
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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 RoleWe are seeking a talented Data Scientist to join our Credit Risk Modeling team. In this role, you will develop, enhance and test our models for use in new customer acquisition and managing our existing customer portfolio. Our team focuses on ways to drive growth while balancing risk. You will independently dive into open-ended problems in order to present recommendations to executives and actively manage the credit models and offer generation that power Enova's business. 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. Our models power our lending decisions, providing critical risk insight to enable competitive and profitable loan offers. Your role will be essential in improving and managing this fundamental area of our business.
Key ResponsibilitiesCompensation:
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:
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.
Sourced by ZipRecruiter
Advertising and public relations services
51 - 200 Employees
New Providence, NJ, US
2002
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.
