Data Analyst/Operational Analyst

4 weeks ago

Portland, United States Portland General Electric Company Full time

Job Function: In this role, you'll track metrics and analyze data to promote operational efficiency and inform business decisions.

Key Job Information Operational Analyst 6699 Grade 6 and Data Analyst 7136 Grade 6

Career Level: P2 Intermediate Professional Requires expanded professional-level knowledge and experience in own area; incumbents continue to acquire higher-level knowledge and skills Expands on high-level knowledge of the company, processes and customers Solves a range of more complex problems Analyzes possible solutions using advanced knowledge and applying protocols Operates independently and receives only a moderate level of guidance and direction

Key Responsibilities:

Reporting:

Develops and runs reports in response to identified business needs. Decides which data is needed. Translates business needs into analytics/reporting requirements to support executive decisions and workflows with required information. May pull data from multiple systems. Develops reporting format to meet user needs using data and visuals in response to business needs. May provide data for compliance reporting. Ensures data security and integrity.

Strategy and Planning:

May provide data and analysis to support development of department metrics and long-range planning. May use data to recommend new or modified operational performance metrics.

Data Management:

Depending on specialty area assigned, may track data related to budget, position management and/or operational performance metrics. Proactively mines data warehouses to identify trends and patterns and generates insights for business units and senior leadership.

May administer database or other data repository. Identifies systems issues and decides which to escalate. May obtain data from external studies or sources. May do some system or database coding or configuration depending on position.

Analysis:

Analyzes data from multiple sources to develop operational metrics. Conducts benchmarking and identifies differences. Creates visuals and other means to explain data trends. Identifies and explains data trends, assumptions, and anomalies. Identifies risks and recommends mitigation strategies. Researches and implements cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence to make data analysis more efficient. Determines requirements that will be used to train and evolve deep learning models and algorithms

Consulting:

Responds to department information requests and suggests additional data to meet business needs. Identifies gaps in data, metrics, or processes. Develops and tracks progress toward metrics. Recommends operational process improvements. Determines which data is needed to respond to business requests for information. Distributes best practices to analytics and product teams and provides consultations for their data-based experiments.

Projects and Initiatives:

Supports projects by determining which data is needed and providing it to appropriate subject matter experts. May lead department data-driven projects.

Education/Experience/Certifications:

Education Requires a bachelor's degree in business, finance, mathematics, statistics, computer science, psychology, or other related field such as economics, physics or operations research. Master's or PhD is a preferred qualification.

Experience Typically two or more years in statistics, finance, process improvement, project management or related field.

Knowledge, Skills, Abilities:

Functional Competencies

  • Intermediate knowledge of statistics, machine learning, metrics and data (e.g., correlation coefficients, etc.)
  • Basic skills in using analytic tools including forecasting, predicting trends and gaining insights using past and current data
  • Intermediate skills in developing and managing dashboards and reports in Tableau
  • Basic Technical knowledge of Tableau Products and versions including Tableau Server, Tableau Public, Tableau Online, Tableau Desktop
  • Basic Knowledge of data architecture, data modeling, data mapping, data analysis, and data visualization
  • Basic skills in  conducting statistical analysis with advanced statistical software, scripting languages, and packages
  • Basic skills in building and deploying predictive models, web scraping, and scalable data pipelines
  • Intermediate skills using data systems specific to department
  • Working skills in managing competing priorities
  • Intermediate skills in synthesizing information and complex data and communicating to diverse audiences
  • Intermediate knowledge of PGE's operational practices
  • Intermediate skills in project management
  • Intermediate knowledge of data integrity and security
  • Working customer focus skills
Read the full posting.

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