PURPOSE: To provide data science services to the Samaritan Ministries International Business Intelligence department to help continuously improve the experience we provide our members.
PRIMARY RESPONSIBILITIES AND DUTIES
- Explore and extrapolate advanced business intelligence insights using mathematics, statistical analysis, textual analytics, machine learning, and predictive analysis.
- Design, create, and explain statistical models, algorithms, and forecasts in support of strategic ministry planning efforts.
- Develop ministry A/B testing framework and test model quality.
- Assist in the design and administration of ministry programs, processes, and applications.
- Collaborate with the data team to build, validate, and automate data sources.
- Advocate for proven statistical standards and practices.
Performs other related duties, as assigned
Education & experience
Prefer candidates with at least a master’s degree from an accredited university or the equivalent in education and experience.
Knowledge, Skills, Abilities
- Collaborative, eager to learn, share knowledge, and adaptable.
- Maintains a humble, Christ-centered attitude.
- Excellent mathematical, machine learning, and statistical skills.
- Strong problem solving skills with an emphasis on product development.
- Experience working with and creating data architectures.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) along with their real-world advantages and drawbacks.
- Ability to convey complex information and coach others in best practices for statistical modeling and forecasting.
- Excellent listening skills coupled with an ability to ask good questions, understand concerns, and bring resolution.
- A professional attitude with an ability to quickly develop a rapport with others.
- Agreement with Samaritan Ministries’ vision and objectives.
- Maintains confidentiality.
- Prefer candidates with proficiencies in the following software: MSSQL, Python, and Tableau.
This position would require travel every so often to the office.