Data Analyst

Our client is a fast-growing fintech company in commercial lending. Its data science team writes the rules that run the company’s automated decision engine, which drives credit, risk, and account decisions every day. As a Data Analyst I, you will use Python and SQL to analyze data, help build and test new rules, and track how those rules perform once they are live. This is an early-career role with real mentoring from data scientists and senior analysts. Recent grads with solid Python and SQL fundamentals are encouraged to apply. What You Will Do

• Write SQL and Python to pull, clean, and analyze the data that feeds decision engine rules.
• Work with data scientists and senior analysts to build, back-test, and validate new rules and rule changes before they launch.
• Monitor A/B tests and live rule changes, and report on how they are performing against expectations.
• Build and maintain recurring reports and dashboards that track key business and portfolio metrics.
• Answer ad-hoc questions from risk, credit, and operations partners with clear, plain-language write-ups.
• Run data quality checks and flag issues before bad data reaches a rule or a report.

• Learn the company’s data, its decision engine, and the lending business behind both., People who like writing code to answer questions and want to understand the business behind the data. Typical backgrounds include junior data, reporting, BI, risk, credit, or underwriting analyst roles, along with recent grads from quantitative programs who have done real work in Python and SQL. If you would rather avoid coding or prefer highly repetitive work, this probably isn’t the right fit. Room to Grow The team has a defined career path for analysts, with room to move up through Data Analyst II, III, and senior levels into lead roles. The rules you write go into production and directly affect how the company lends, so your work has visible impact from early on. Work Arrangement and Other Details

• Onsite at either the Sioux Falls or Sandy office for your first six months. After that, a hybrid schedule may be available depending on business needs, your performance, and leadership sign-off.
• Regular hours are Monday through Friday, 8:00 AM to 5:00 PM. Expect the occasional evening or weekend when a deadline calls for it.
• Candidates willing to relocate are welcome to apply, but the company does not offer relocation assistance.
• You must be authorized to work in the U.S. without employer sponsorship, now or in the future.

Data Analysis, Data Science, Commercial Loans, Credit Risk, Data Analysis, Testing, SQL (Structured Query Language), Mentoring, Python Programming/Scripting Language, A/B Testing, * A four-year degree from an accredited institution.

• Working Python for data analysis (pandas, NumPy, or similar), whether from coursework, internships, or your own projects.
• SQL fundamentals, including joins, aggregations, and filtering.
• Enough statistics to read an A/B test result and know when a difference is real.
• Strong Excel skills.
• Basic familiarity with Tableau, Power BI, or another visualization tool.
• The ability to explain what the data shows to people who don’t work with it every day.
• Careful attention to detail, plus the ability to manage several requests and hit deadlines.

Nice to Have

• A degree in data science, statistics, mathematics, computer science, economics, data analytics, business analytics, MIS, industrial engineering, operations research, or another quantitative discipline.
• Internship or job experience writing Python or SQL against real business data.
• A GitHub profile or project portfolio you can share.
• Experience with Jupyter notebooks or Git.
• Any exposure to rules engines, credit decisioning, or A/B testing.
• Interest or background in fintech, lending, banking, or credit and risk analytics.