Job Profile Summary:

The Production Engineering Data Analyst works to generate data-driven insights across various stakeholders and functional teams across the organization. They seek to automate manual processes and will also proactively explore and develop new and innovative methods to retrieve, visualize, and analyze data from various operational, geological, and financial sources. In this role, Data Analysis works with greater autonomy on routine analyses and contributes to larger projects, providing reliable analysis that informs team-level decisions.

Responsibilities:

· Builds ad hoc queries and modifies and optimizes existing queries to answer slightly more complex questions.

· Builds new dashboards and reports from established data models.

· Conducts descriptive analysis to identify trends, patterns, and anomalies in datasets.

· Begins to document data sources and analytical processes.

· Collaborates independently with a broader range of stakeholders, proactively identifying opportunities to enhance analytical datasets, visualizations, and tools.

· Leads efforts to investigate, document, and resolve complex data issues, coordinating with data owners and IT to implement sustainable solutions.

· Applies advanced analytics techniques to larger, more complex data sets, providing actionable insights that inform team and department-level decisions.

· Designs and executes advanced statistical analyses, and begins to customize models to address unique business challenges.

· Develops and deploys GenAI-powered tools and agents to automate recurring analyses and reporting tasks.

· Recommends and pilots improvements to data collection and reporting processes, measuring impact and iterating as needed.

· Mentors junior team members, delivers informal training, and contributes to the development of team data literacy resources.

Skillset:

· AI: Independently uses AI to accelerate personal workflows, such as code generation, debugging, and drafting report summaries.

· Process: Identifies and suggests minor improvements to personal and team-level data workflows.

· Advanced proficiency in scripting languages, able to write efficient, reusable code and automate routine analyses.

· Deepens expertise in multiple analytics platforms and tools, and begins integrating data across systems for more comprehensive analysis.

· Applies advanced visualization techniques to larger and more complex datasets, tailoring visualizations to audience needs.

· Demonstrates strong troubleshooting skills, independently resolving data and technical issues.

· Translates complex analyses into actionable recommendations for teams and departments.

· Communicates technical findings effectively to both technical and non-technical audiences.

· Facilitates small group discussions and knowledge sharing sessions.

Education:

· Bachelor’s Degree from an accredited college or university in Management Information Systems, Data Analytics, Information Science/Management, Economics, Finance, Accounting, Geoscience, Engineering, or related degree.

Competencies:

· Technical Execution: Independently executes and adapts queries; automates routine data tasks.

· Tool Proficiency: Integrates multiple tools and platforms for more complex analyses.

· Data Quality: Identifies and resolves common data issues; documents and shares solutions.

· AI & Automation: Applies AI tools to automate repetitive processes and enhance efficiency.

· Stakeholder Engagement: Proactively supports cross-functional teams; anticipates stakeholder data needs.

· Communication: Tailors data presentations for different audiences; explains analytical methods.

· Learning: Shares knowledge with peers; participates in team training.