Senior Specialist, Data Science

About the role

Design, develop, and implement data-driven models and analytical frameworks to generate predictive insights and support strategic business decision-making. Apply statistical methods, data mining techniques, and analytical tools to analyze large datasets and identify patterns, trends, and correlations. Develop and optimize data pipelines and data processing workflows using cloud platforms (e.g., AWS) and data warehouse technologies (e.g., Snowflake) to support scalable analytics.

Perform predictive modeling, scenario analysis, and forecasting to evaluate business performance, risks, and opportunities. Establish and maintain data quality frameworks, validation processes, and monitoring systems to ensure accuracy, reliability, and consistency of analytical outputs. Design and implement data models, including structured datasets and analytical data marts, to support advanced analytics and reporting use cases.

Develop and deliver dashboards and data visualizations using tools such as Power BI or 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.

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, or position involving data analysis, data management, and database design.
• 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.

Pay

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