Data Scientist

At PGE, our work involves dreaming about, planning for, and realizing a smarter, cleaner, more enduring Oregon neighborhood. Its core to our DNA and we haven’t stopped since we started in 1888. We energize lives, strengthen communities and drive advancements in energy that promote social, economic and environmental progress. We’re always on the lookout for people passionate about leading and being a part of teams that are advancing innovative clean energy solutions that are also affordable and accessible to all.

Summary

The Advanced Energy Delivery Technology Solutions (AEDTS) team at Portland General Electric plays a crucial role in advancing our clean energy future through smart grid technology. We operate in two key areas:

This dual approach enables the team to drive PGE's goals of decarbonization, electrification, and operational efficiency across the organization while also maintaining critical systems for reliable service delivery.

Our team is seeking a highly motivated and talented Data Scientist to join our growing team. In this role, you will play a critical part in driving data-driven decisions across the organization. You will leverage your strong analytical and technical skills to extract meaningful insights from complex data sets, develop and deploy predictive models, and collaborate with cross-functional teams to solve challenging business problems.

Career Level Summary

Data Scientist 6969

Grade 7

Career Level: P3

Career 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

Analyses possible solutions using advanced knowledge and applying protocols

Operates independently and receives only a moderate level of guidance and direction

Key Responsibilities

Data Collection & Preparation:

Participates/assists in identifying what data is available and relevant, including internal and external data sources; supports data collection, integration and retention requirements based on the input received; ensures information used follows PGE compliance, access management and control policies and meets PGE qualification and assurance requirements. Handle missing values, outliers and inconsistencies. Transform data with feature engineering, normalization and dimensionality reduction.

Data Analysis & Modeling:

Conduct exploratory data analysis (EDA): Identify trends, patterns, and relationships within the data.

Develop and implement statistical and machine learning models: Regression, classification, clustering, time series analysis, deep learning.

Evaluate model performance: Use appropriate metrics (accuracy, precision, recall, F1-score, AUC, etc.) and techniques (cross-validation, A/B testing).

Model Deployment & Monitoring:

Deploy models into production environments: Integrate models into existing systems or build new applications.

Monitor model performance over time: Track key metrics, identify and address issues (e.g., concept drift, data bias) towards business outcomes.

Maintain and update models: Retrain models with new data and improve their accuracy.

Communication & Collaboration:

Collaborate with stakeholders: Works with business stakeholders to identify the business requirements and expected outcomes. With business stakeholder support, models and frames meaningful and impactful business scenarios for critical business processes and/or decisions.

Collaborate with cross-functional teams: Work closely with engineers, product managers, and business analysts.

Communicate findings effectively: Present results to stakeholders (business leaders, engineers, etc.) through reports, presentations, and visualizations.

Stay updated on the latest advancements: Keep abreast of new technologies, tools, and techniques in the field of data science.

Qualifications

Education Requires a MSc or PhD in mathematics, statistics or computer science or related field, such as physics, economics or operations research.

Experience Typically, five or more years in data science or related field; prototyping and implementation experience preferred.

Certifications, Licenses and Training Intermediate programming skills, including experience with Hadoop MapReduce or other big data frameworks, Java, Python, statistical modeling, SQL and text mining or machine learning. Knowledge of cloud AWS/GCP/Azure and automation framework preferred.

Competencies

Functional Competencies:

General Competencies:

Physical, Schedule/Attendance and Cognitive Demands

Cognitive Level: Intermediate: Consistent use of relevant principles to solve practical problems and to deal with a variety of concrete variables in situations where only limited standardization exists.

Cognitive:

Schedule/Attendance:

Physical Capabilities:

Stairs (over 10 steps)

Environment:

Office

PGE supports hybrid flexible work arrangements; and will have a combination of in-the-office and working offsite. However, these arrangements may change due to business needs or changes in responsibility.

We are interested in every qualified candidate who is eligible to work in the United States to apply. However, we are not able to sponsor visas for this position.

Compensation Range:

$114,975.00 - $191,625.00

Actual total compensation, including a performance based incentive bonus, is commensurate with experience, skills, qualifications, education, training, and internal equity. While we anticipate the selected candidate for this position will fall towards the middle or entry point of the compensation range, the decision will be made on a case-by-case basis.

PGE believes in rewarding dedicated performance. We provide a total rewards package that is designed to reward your contributions to the company, and, at the same time, support your well-being and professional development, both now and into the future. To find out more, click here.