United Federal Credit Union

* Candidates must be based in the United States and reside in one of the following states: Arkansas, Florida, Georgia, Idaho, Indiana, Kansas, Kentucky, Michigan, Nevada, North Carolina, Ohio, Oklahoma, Pennsylvania, South Carolina, Tennessee, Texas, Virginia, and Wisconsin.
* To qualify, applicants must be legally authorized to work in the United States, and should not require, now or in the future, sponsorship for employment visa status. 
 
 

Summary 
 
GENERAL SUMMARY (What is done and why) 
 
The Data Scientist is highly proficient in managing complex data sets, building advanced analytical models, using various statistical and data exploration practices, and productionizing Machine Learning (ML) & Generative Artificial Intelligence (GenAI) systems to answer complex business questions. The Data Scientist displays curiosity, creativity, and the ability to organize stakeholder problems into clear business objectives for which they can create analytics solutions that deliver immediate value. With a strong desire to get ideas off the drawing board, the Data Scientist quickly develops prototypical solutions that can be improved via collaboration with teammates and cross-functional stakeholders. This position is responsible for defining requirements, data gathering, design, development, and management of predictive models and advanced dashboard applications. The Data Scientist provides factual and conceptual analysis/interpretation of specialized business/member data, consider potential opportunities, and develop appropriate value-added recommendations throughout the predictive analytics lifecycles all the way from insights to action. 
 
ESSENTIAL FUNCTIONS, IN PRIORITY ORDER (Majority of duties, but not meant tobeall inclusive or prevent other duties from being assigned as necessary) 
 


* Support the implementation of new models and model refreshes. Take ownership of all predictive and descriptive statistical models: this includes but is not limited to the model selection and scoring processes, suitable approaches and objectives, establishing controls around the quality of data and measures, creating process checks, scoring output, designing and tracking impactful KPIs, monitoring and retraining models, and tailoring the effectiveness of predictive models.Time: 40%
* Recommend enhancements to our predictive models by gaining an understanding of competing models, current model performance, and feedback from stakeholders. Time: 20%
* Perform strategic analysis, using a variety of data sources, to help management make informed business decisions by using statistical methods to identify patterns and trends. Time: 10%
* Serve as a SME and lead the development and management of new and existing data visualizations and interactive dashboards to provide insights at scale, solving for analytical needs with a bias for execution. Time: 10%
* Take the lead with cross-functional stakeholders to understand their business needs, formulating and completing end-to-end analysis that includes data gathering, analysis, and effective presentation and communication of findings and recommendations from the models/dashboards to multiple levels of stakeholders. Time: 10%
* Collaborate with the Data Management and Reporting & Analytics teams, as well as other team members for the development of data and analytics related solutions. Time: 5%
* Perform other duties as required by management. Time: 5% 
 
 

Required 
 
EDUCATION (Minimumeducationrequiredto perform the dutiesof this position) 
 


* Bachelor's degree in Mathematics, Statistics, Data Science, Computer Science, Finance, Accounting or related technical field or seven years of related work experience required.
* Graduate-level degree with concentration in a quantitative discipline such as Mathematics, Statistics, Data Science, Computer Science, Economics, Business Analytics, or Operations Research preferred. 
 
 

In Additiontothe Educationrequirement 
 
EXPERIENCE (Minimum experience requiredto perform the dutiesof this position) 
 


* 3 or more years of experience using SQL, relational databases, and normalization to build reports, mine/clean data, and analyze data, preferably within Snowflake or SQL Server environments.
* 3 or more years of quantitative experience using statistical packages such as R or Python to run Data Science processes, from data gathering to model building & scoring to results tracking.
* Hands-on experience deploying models in production environments using MLOps tools and practices, specifically model versioning, CI/CD, containerization, orchestration, monitoring, and alerting.
* Professional experience building reports, performing data analysis, and building interactive data visualizations and dashboards, preferably in the financial services industry.
* Experience using LLMs or AI Agents to achieve an objective in a professional setting preferred.
* Business acumen to articulate and answer business questions backed by statistics to arrive at the right answer.
* Solid knowledge of Qlik Sense or similar dashboarding/analytics tool with the ability to develop, maintain, and manage dashboards, advanced reporting, analytics, and other analytics solutions.
* Expertise in data storytelling and the delivery of practical data insights in a compelling manner articulating findings clearly and concisely in presentations, discussions, and visualizations.
* Demonstrated ability in creating technical solutions to solve complex business problems. 
 
 

KNOWLEDGE, SKILLS AND ABILITIES (Minimumtechnical and communicationskill levels and licenses/certificates normally required toperform the duties of this position) 
 


* Must have excellent oral and written skills, being able to communicate effectively on both a technical and business level.
* Experience working with databases including proficiency in SQL.
* Knowledge of emerging statistical tools and technologies (e.g., R, Python, Data Robot, etc.).
* Knowledge of Statistical and Data Science model types (e.g., Classification, Regression, etc.).
* Knowledge of analytical reporting tools and technologies (e.g., Qlik, Tableau, Power BI, etc.).
* Strong analytic skills and ability to develop, and implement analytical data models, dashboards and reports using analytics tools to empower our internal customers to analyze data and make informed business decisions.
* Deep interest and aptitude for analyzing data and converting it into insights that drive business decisions at all levels of the organization. 
 
 

Preferred Qualifications 
 


* Familiarity with Snowflake and Snowpark Python for scalable data science workflows.
* Strong understanding of data privacy, compliance, and ethical Data Science/AI practices in financial services, as relates to regulations and requirements of the NCUA.
* Knowledge of emerging AI terms and ideas (e.g., LLMs, Agents, MCP, etc.).
* Understanding of GitHub or related version control/repository infrastructure. 
 
 

What You’ll Influence 
 


* Member engagement/personalization strategies, operational efficiencies, and digital transformation initiatives.
* The continuous improvement of our analytics capabilities, data-driven culture, and AI-assisted evolution.
* The usage and development of our data & analytics stack (Snowflake, Snowpark Python, Data Robot, Qlik Sense) to optimize Data Science initiatives (Next Best Action, Attrition, etc.).
* Reinforcement of Responsible AI / Governance standards: Model documentation, explainability, bias testing, and model inventory. 
 
 

_Required Competencies 
 
_

* Curiosity and eagerness to learn
* Outstanding collaborator
* Problem Solving
* Drive for Results
* Time Management
* Interpersonal Savvy
* Customer Focus
* Integrity and Trust
* Self-Development
* Business Acumen
* Project Management 
 
 

_Mental Requirements 
 
_

* Ability to work under pressure
* Ability to work independently
* Ability to own a project from end-to-end
* Proven problem-solving abilities
* Ability to understand and relate activities to strategic objectives
* Ability to concentrate in a multi-task environment
* Ability to maintain a positive attitude and professional image 
 
 

_Tools and Equipment Used 
 
_

* All available general office equipment as needed
* All available computer software and hardware as needed
* PC, scanner, and accessories
* Research tools and services 
 
 

WORKING RELATIONSHIPS/CONTACTS (Positions withwhich incumbent has frequent contact) 
 


* Daily, personal/written/phone contact with Director of AI & Data Science
* As necessary, personal/written/phone contact with other department managers
* As necessary, personal/written/phone contact with Credit Union staff
* Daily, personal/written/phone contact with vendors
* Occasional, personal/written/phone contact with community agencies and consultants 
 
 

PHYSICAL DEMANDS (Physical effort generally associated with this position) 
 
Work involves standing and walking for brief periods of time, but most work is done froma seated position. There is potential for eyestrain from prolonged work at the computer. Deadlines, workloads, and pressure to achieve goals may cause increased stress levels. Ability to lift an average of 35 pounds may be required when moving boxes of printed materials. 
 
WORKING CONDITIONS (Typicalworking conditions associated with this type of workandenvironmental hazards, if any, that may be encountered inperforming the duties of this position) 
 
_Internal_ \- Work is normally performed in climate -controlled office environment, where exposure to conditions of extreme heat/cold, poor ventilation, fumes and gases is limited. Noise level is moderate and includes sounds of normal office equipment (computers, telephones, etc.). No known environmental hazards are encountered in normal performance of duties. Length ofday is unpredictable; long hours may be required to accommodate deadlines, special meetings. 
 
_External_ \- Some travel is required; however, information on environmental conditions is not available. 
 
EOE/Vets/Disability

Data

Data Science

Python

Data analytics

Database

Analysis

Machine learning

Statistics

Microsoft SQL Server

Mathematics

Continuous Integration

Tableau

Hardware

Software Development

Problem solving

Testing

Research

Support

Version control

Accounting

Project management

Team collaboration

Relational Database

Communications

Operations

Compliance

Data privacy

Time management

Storytelling

Infrastructure

Project documentation

Community management

MLOps

Qlik Sense

Snowflake

Industrial Robot

Power BI

Generative AI

Statistical Analysis

Data Visualization

Predictive modeling

Statistical Programming

Data Management

Operations Research

Data Scientist