SAS Data Scientist

DESCRIPTION and RESPONSIBILITIES

The Data Scientist focuses on using advanced analytics in support of the client’s strategic objectives. This position is responsible for performing sophisticated data analytics (encompassing data mining, statistical analysis, predictive analytics, for example), and developing, documenting and supporting the deployment of quantitative models and other analytics tools. Identifies actionable insights from data that measurably improve business outcomes and/or reduce risk. Collects and prepares data for analysis, performs exploratory to advanced predictive and/or modeling analytics, and identifies data relationships (patterns and trends). Provides consultation to business leaders and other stakeholders on how to leverage analytic insights to build actionable strategies. Projects may include but not be limited to: automated credit decisioning, risk rating models, loan performance forecasting and analytics and model validation.

QUALIFICATIONS – ESSENTIAL

• Bachelor's Degree in Mathematics, Finance, Statistics or Economics (or equivalent). Advanced degree or in analytics field, certifications in analytics, or Charter Financial Analyst designation preferred

• 5 or more years of progressively responsible experience in risk management, credit, finance, or data science.

• At least one year of experience in credit risk modeling or equivalent.

• 5 years Developing and implementing models for these purposes

• Experience with FICO Model Development is preferred.

• Strong statistical acumen with in-depth knowledge of risk modeling. Experience with statistical programming languages such as R, Python, SAS, etc.

• Strong computer literacy and proficiency in data querying tools (e.g., SQL, SAS, etc.)

Knowledge of: Statistical methods, time-series analysis, machine learning, and programming; principles, policies and practices applicable to agricultural and residential lending; critical economic, political and industry issues; loan origination and accounting systems; and business automation and relational databases.

Skills in: Business computer applications; advanced data analysis and validation; data science; computer-based modeling and validation; problem solving; decision making; verbal and written communication; interpersonal skills; tact and diplomacy; mediating and influencing solutions to problems; and relevant software such as SQL, VBA, R and SAS.

Ability to: Be innovative and creative balanced with logic and objectivity; positively influence others; and exercise sound judgment. Be flexible, efficient, disciplined and accurate; work with interruptions; work independently; achieve goals; accept and implement corporate strategies; demonstrate corporate values; relate positively to others; listen; work under stress; overcome objections; and professionally represent the client. Conduct increasingly advanced computer analysis in analyzing and developing solutions to complex issues and risks; aggressively leverage technology; and thoughtfully evaluate, accept and manage balanced business risks.

PRIMARY RESPONSIBILITES:

• QUANTITATIVE MODELING: Participate in the design, implementation and maintenance of automated credit decisioning and loss forecasting models. For deployed models, develop and execute ongoing model validation processes in accordance with client’s Model Risk Management and Model Governance policies and industry best practices.

• SPECIALIZED AND ADVANCED ANALYSIS: Applies advanced analytical skills and experience to research complex topics, design analysis methodologies, and apply problem solving skills in performing ad hoc analysis projects.

• CREDIT & RISK EXPERTISE: Continually build expertise in agricultural and consumer credit, finance and technology to support being an active partner and risk management resource for the Credit Department and other departments across the Association.

• COLLABORATION: Represent the Risk Management department on applicable Association committees, workgroups or project teams. Coordinate with other Farm Credit System (FCS) institutions and FCS workgroups as applicable.

• Corporate mission and values: Embraces and represents the mission and values of the client and complies with its conduct, security and confidentiality policies and procedures.

• OTHER DUTIES: Performs other duties as assigned.

• Lead development and implementation efforts on models designed for capital management.

• The incumbent will gather and meet business requirements, construct applicable and accurate development datasets, and explore, estimate, and test alternative approaches in order to set methodology.

• Make certain that independent and effective validation for conceptual soundness takes place prior to model implementations and establish ongoing monitoring routines and outcomes analyses.

• Good written and spoken communications skills in English and thought-leadership skills.