Seasonal Python Analyst Jobs in Illinois (NOW HIRING)

Empowered to live. Inspired to work.
Compeer Financial is a member-owned cooperative located in Illinois, Minnesota and Wisconsin. We bring together team members with a variety of backgrounds and experiences to help provide financial services to support agriculture and rural communities. Join us in a culture that not only promotes meaningful work and professional development, but provides a flexible, hybrid work environment and excellent benefits, which empower you to thrive both personally and professionally.
How we support you:

• Hybrid model - up to 50% work from home
• Flexible schedules including ample flexibility in the summer months
• Up to 9% towards 401k (3% fixed Compeer contribution plus up to 6% match)
• Benefits: medical, dental, vision, HSA/FSA, life & AD&D insurance, short-term and long-term disability, wellness program & EAP
• Vacation, sick leave, holidays/floating holidays, parental leave, and volunteer paid time off
• Learning and development programs
• Mentorship programs
• Cross-functional committee opportunities (i.e. Inclusion Council, emerging professional groups, etc.)
• Professional membership/certification reimbursement and more!

Casual/seasonal & intern team members are not eligible for benefits except for state-mandated programs.
To learn more about Compeer Financial visit www.compeer.com/careers.
Where you will work:This position offers a hybrid work option up to 50% and is open to any Compeer office location in Illinois, Minnesota and Wisconsin.
The contributions you will make:
This position develops, organizes, and maintains models to support business insights and strategic decision making across the organization. Applies advanced analytic methodologies within an integrated stress-testing framework, economic capital model (credit, market and operational risk), expected credit loss model, and scenario-based forecasts, and evaluates other business-related statistical relationships. Uses quantitative methods to research modeling methodology for the development, refinement and parameter updates for risk/reward-based framework.
A typical day:

• Examines large data sets to identify patterns, anomalies, relationships and trends. Conducts ad hoc research and analysis.
• Utilizes analytic tools (i.e. Python, SQL), data query tools to build test, evaluate, organize and analyze large, diverse and imperfect data sets.
• Develops data structures to support the generation of business insights and strategy and translate data findings into actionable recommendations and improvements.
• Gathers and analyzes data from multiple internal and external sources to identify trends and predict responses.
• Continuously evaluates industry trends for opportunities to utilize new technologies and data sources and recommend strategies to implement these enhancements in the data environment.
• Conducts complex analytical studies with collaborative help from others, develops advanced quantitative models, and make strategic recommendations to improve performance, drive cost savings and revenue growth, and maximize profits in support of operational, risk, credit, retention, sales, and marketing effectiveness.
• Supports the model development process for internal business clients from conceptualization through data exploration and implementation. Translating results into meaningful solutions.
• Work with new and existing third-party vendors to implement, validate, and maintain decision models.
• Leverages traditional quantitative approaches such as regression, decision trees, clustering, etc. as well as progressive techniques to solve business problems.
• Conducts statistical and economic analysis to understand key drivers impacting the financial and risk position of the organization.
• Works with model owners to conduct internal model validations following regulatory guidance and industry best practice. Documents validation processes and results.
• Conducts back testing and validation activities and provides data analysis to support assumptions and mitigate limitations.

The skills and experience we prefer you have:

• Bachelor's degree in computer science, information systems, mathematics, statistics, econometrics or related field or an equivalent combination of education and experience sufficient to perform the essential functions of the job.
• Minimum of 3 years of experience in risk management modeling or advanced analytics and in-depth model development experience using econometric and statistical modeling techniques.
• Familiarity with statistical techniques including regression analysis, decision trees, and stochastic processes.
• Proficiency with Python highly preferred; or experience with at least one major statistical software program required.
• Experience with data query or visualization tools preferred (i.e. SQL, Power BI).
• Ability to communicate and explain complex quantitative modeling content to stakeholders.
• Proven ability to work under minimal supervision and demonstrated efficiency in meeting deadlines.
• Strong listening, written and verbal communication skills, with ability to communicate at all levels of the organization.

How we will take care of you:
Our job titles may span more than one career level (associate, senior, principal, etc.). The actual title and base pay offered is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role is eligible for variable compensation and other benefits.
Base Pay
$75,600-$114,200 USD
Compeer Financial is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.
Must be authorized to work for any employer in the United States. Compeer is unable to sponsor or take over sponsorship of an employment visa at this time.
Click here to view federal employment laws applicable for applicants.