Decision Scientist

Artemis Connection; San Antonio (TX); On-site; USD 80,000 - 110,000; Full time

Job summary

A leading analytics firm is seeking a Decision Scientist for a 3-4 month contract in San Antonio, Texas. The role involves tackling complex analytics challenges for a multi-state restaurant chain, focusing on advanced analytics, data visualization, and collaboration. Ideal candidates will have strong skills in SQL, Python, and statistical modeling. Responsibilities include mentoring team members, data preparation, producing actionable insights, and operationalizing analytics into business processes. This position emphasizes leadership and fostering a culture of analytics.

Qualifications

• BA/BS in Statistics, Mathematics, Computer Science, or related field.
• Strong proficiency in SQL, SAS, Python, or R.
• Experience with cloud data platforms and BI tools required.

Responsibilities

• Drive team engagement and mentorship in analytics best practices.
• Extract and clean data from cloud and on-premise systems.
• Produce reports and dashboards from structured data sources.
• Apply statistical techniques to drive business decisions.
• Operationalize insights by integrating analytics into business processes.

Skills

SQL

SAS

Python

R

Microsoft Excel

Microsoft PowerPoint

Data Visualization

Statistical Analysis

Education

BA/BS in Statistics

BA/BS in Mathematics

BA/BS in Computer Science

BA/BS in Engineering

BA/BS in Economics

BA/BS in Psychology

BA/BS in Quantitative Social Science

Tools

Azure Data Lake

SQL Server

Oracle

AWS

Tableau

Power BI

Job description

Overview

Role: Decision Scientist

In this 3-4 month contract engagement, we're looking for an experienced data scientist to tackle complex, high-visibility problems for one of our clients, a multi-state restaurant chain. You will leverage advanced analytics to drive the development and optimization and support key organizational initiatives.

Responsibilities

Leadership & Team Development

• Drive engagement, development, and performance of team members.
• Mentor and coach data analysts and decision scientists in best practices, methodology, and privacy/security standards.

Data Preparation & Management

• Extract, synthesize, and clean data from multiple sources, including Azure Data Lake, SQL Server, Oracle, and other legacy systems.
• Conduct exploratory data analysis, aggregate data, and ensure privacy-compliant handling of 1st, 2nd, and 3rd-party customer data.
• Guide the team in preparing unfamiliar or complex datasets for analysis.

Data Visualization & Communication

• Produce standard and custom reports, charts, graphs, and dashboards from structured data sources.
• Translate complex data into actionable insights and effectively communicate findings to non-technical stakeholders.
• Mentor the team on best practices for visualization, storytelling, and privacy-compliant reporting.

Data Manipulation & Modeling

• Procure and reshape large-scale, complex datasets for analysis across cloud (AWS, Azure) and on-premise systems.
• Identify anomalies, data issues, and work cross-functionally to resolve them.
• Apply statistical and predictive modeling techniques (regression, clustering, survival analysis, anomaly detection, factor analysis, etc.) to drive business decisions.
• Coach team members on code, methodology selection, and model development.

Business Understanding & Insights Operationalization

• Develop deep understanding of business problems and key metrics.
• Partner with stakeholders to identify core questions and design optimal solutions.
• Operationalize insights by integrating analytics into business processes and driving KPI-focused improvements.
• Lead analytics refresh exercises and model/rule tuning processes.

Leadership & Evangelism

• Collaborate across organizational levels to evangelize advanced analytics and decision sciences.
• Foster a culture of curiosity, rigor, and passion for analytics across the team.

Qualifications

We’d love to hear from candidates with:

• Education: BA/BS in Statistics, Mathematics, Computer Science, Engineering, Economics, Psychology, Quantitative Social Science, or similar.
• Technical Skills:
• Strong proficiency in SQL, SAS, Python, or R
• Skilled in Microsoft Office (Excel, PowerPoint)
• Solid understanding of statistics (descriptive, regression, etc.)
• Experience with cloud data platforms (Azure, AWS) and BI tools (Tableau, Power BI)
• Professional Attributes:
• Ability to handle and maintain the confidentiality of sensitive information
• Strong analytical, problem-solving, and communication skills