Decision Scientist

Artemis Connection•San Antonio, TX

101d

About The Position

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.

Requirements

BA/BS in Statistics, Mathematics, Computer Science, Engineering, Economics, Psychology, Quantitative Social Science, or similar.
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)
Ability to handle and maintain the confidentiality of sensitive information
Strong analytical, problem-solving, and communication skills

Responsibilities

Drive engagement, development, and performance of team members.
Mentor and coach data analysts and decision scientists in best practices, methodology, and privacy/security standards.
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.
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.
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.
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.
Collaborate across organizational levels to evangelize advanced analytics and decision sciences.
Foster a culture of curiosity, rigor, and passion for analytics across the team.