Senior Specialist, Data Science

Tableau to communicate insights to stakeholders; collaborate with business and technical stakeholders to translate business requirements into data-driven solutions and analytical models; conduct root cause analysis of data and performance issues, and implement data-driven solutions to improve system performance and business outcomes; evaluate and recommend advanced analytics tools, technologies, and methodologies to enhance data science capabilities; apply advanced SQL and programming techniques to extract, manipulate, and analyze data for modeling and reporting purposes; support data governance initiatives, including data lineage, metadata management, and compliance with data standards and regulatory requirements; present analytical findings, models, and recommendations to stakeholders, including executive leadership, to support decision-making; drive continuous improvement through automation, optimization of data processes, and implementation of scalable analytics solutions. Salary

$120,723 - $140,000 per year.

MINIMUM REQUIREMENTS: Bachelor’s degree or its U.S. equivalent in Computer Science, Information Systems, Computer Engineering, or a related field, plus 5 years of professional experience as a Sr. Data Analyst, Data Modeler, or any occupation, job title, position involving data analysis, data management, and database design.

Must also have experience in the following: 5 years of professional experience writing, optimizing, and troubleshooting advanced SQL queries; including complex joins, aggregations, subqueries, stored procedures, functions, and performance tuning in relational databases; 5 years of professional experience performing data manipulation, automation, and statistical analysis, including building robust data pipelines and ETL processes to integrate disparate railroad data sources; 5 years of professional experience documenting SQL queries, logic, data workflows, and analytics results for technical and non-technical stakeholders; 5 years of professional experience working with cross-functional teams (including business, IT, and finance) to gather requirements, clarify business needs, and deliver solutions strictly via SQL; 4 years of professional experience utilizing statistical analysis, including regression analysis, time-series forecasting, applied to rail operations data to generate insights; 3 years of professional experience developing executive dashboards and interactive reports using tools including Power BI or Qlik, to communicate operational insights and performance metrics effectively; 3 years of professional experience in rail transportation operations, including knowledge of industry terminology and processes, and applying this knowledge to support analysis and decision-making in a railroad environment.