Data Scientist

American AgCredit

8d•$88,741 - $150,859•Remote

About The Position

The Data Scientist at American AgCredit is an integral part of the Data Science team within the Treasury and Analytics group, which is a department of the Finance Organization. This role focuses on driving innovation and solving complex problems creatively, directly enhancing the lives of farmers and ranchers by supporting their financial needs and helping them succeed and grow. Through these efforts, the Data Scientist supports American AgCredit’s mission of securing the nation's food supply by providing innovative financial solutions within the agricultural community. The Data Scientist is responsible for developing, implementing and monitoring advanced statistical and machine learning models to support various business functions. This includes creating / maintaining scorecard models, and or optimizing auto-decisioning strategies. The role may also involve developing customer segmentation, lead scoring, churn prediction, and or recommendation models that drive go-to-market strategies. The Data Scientist analyzes specific business opportunities and risks, using quantitative methods to solve complex tasks that improve business performance. In collaboration with a cross-functional team of data analytics and IT professionals, the Data Scientist will deliver AI-powered products that enhance data-driven decision-making, increase productivity, and automate repetitive tasks. As part of this, the role requires leveraging Generative AI to enhance NLP and conversational AI capabilities, building scalable digital assistant solutions. Overall, the Data Scientist plays a pivotal role in empowering the Data and Analytics community, fostering data literacy and self-service capabilities, and driving the organization to foster a culture of evidence-based decision-making.

Requirements

A bachelor’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Computer Science, or a related “STEM” field - Science, Technology, Engineering or Mathematics).
3-7 years of progressively responsible experience in Data Science, Quantitative Modeling, Risk Modeling, Advanced Analytics or Applied Mathematics.
At least 2 years’ experience in Python, or R.
At least 2 years’ experience with Statistics and Machine Learning.
At least 2 years’ experience with SQL.
Expertise in several statistical techniques including regression analysis, decision trees, tree-based models like Random Forest or Gradient Boosting, time series, deep learning, data pipelines and evaluating model performance.
Proficiency with at least one major programing language (Python or R) is required.
Excellent organizational skills and attention to detail.
Excellent written, verbal, persuasive, and interpersonal skills.
A passion for empowering the Data and Analytics community to democratize analytics, foster data literacy and self-service capabilities, and drive towards enhanced Data-Driven Decision Making.

Nice To Haves

Full ownership of an Agile model development process and relationship with the business customer. Examples include understanding the business problem, framing the problem, performing data exploratory analysis and visualization, methodology selection, model testing and validation, implementation, business user training and support, and model monitoring.
Translating results into meaningful solutions to enhance data-driven decision making.
A master’s degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics).
Experience with LLMs, RAG, Agentic AI.
Working knowledge of lending principles and practices, as well as ability to interpret policy, programs and regulations.

Responsibilities

Develop, implement and monitor various statistical and machine learning models to support various business functions.
Support independent model validation efforts in accordance to the model risk management policy.
Partner with a cross-functional team of data, analytics, and development operations (IT) to deliver AI powered products that can help team members be data-driven, increase their productivity and automate repetitive tasks.
Leverage Generative AI (Gen AI) to produce conversational AI capabilities and build scalable digital assistant solutions.
Leverage a broad stack of technologies, such as, Python and or R, SQL, Alteryx, Power BI, Azure Dev Ops or equivalent and more to reveal the insights hidden within large volumes of numeric and textual data.
Maintain documentation for key processes and model components with a focus on standardization of processes that satisfy model risk management, audit, and regulatory requirements.
Build strong collaborative relationships with business teams at AAC as well as other Farm Credit System entities.
Ensure analytics practices meet applicable regulatory, audit, privacy, and cybersecurity standards; participate in remediation and audit readiness.

Benefits

Commitment to agriculture and the communities we serve
Family friendly work environment
Investment in employee development
Medical, Dental and Vision coverage
Outstanding 401k – automatic 3% employer contribution, plus match up to 6%
Generous Paid Time Off (Vacation accrued at 21 days annually, Sick Days accrued at 15 days annually, 12 paid holidays, plus 16 hours of volunteer time)
Competitive Incentive Compensation Plan
Disability & Life Insurance
Employee mental, physical, and financial wellness programs
The position is bonus eligible based on association and personal performance