About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Utilities.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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What You’ll Do

This role is an entry-level/full-time Data Scientist position on an agile squad focused on digital innovation for the electric utility sector. You will build and deploy machine learning and statistical models that deliver actionable insights to improve reliability, customer experience, and operational performance.

• Develop, validate, and productionize machine learning models (classification, forecasting, optimization) using Python and related libraries.
• Work with tabular, streaming, text, geospatial and high-volume data sources; perform feature engineering and data transformations.
• Build and evaluate models using relevant metrics (e.g., F1, ROC AUC, forecasting accuracy) and statistical techniques.
• Collaborate with Data Engineers, other Data Scientists, and business stakeholders to turn analytical results into deployed solutions.
• Conduct experiments, prototype solutions rapidly in cloud environments, and adopt DevOps practices for model deployment.
• Research and recommend new data sources, tools, and methods to improve analytics and automation.
• Communicate technical results clearly to non-technical stakeholders and contribute to cross-functional decision-making.
• Support projects across customer analytics, transmission & distribution reliability, smart meter analytics, and vegetation/forest management using geospatial & imagery data.
• Travel within the service territory as needed and work extended hours on occasion to support business needs.

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What We’re Looking For

Candidates should be comfortable working across the full model lifecycle and in cross-functional teams. Ideal background:

• Bachelor’s degree in a quantitative field (Computer Science, Statistics, Mathematics, Machine Learning); advanced degrees (MS/PhD) are a plus.
• Practical experience with machine learning algorithms (decision trees, random forests, neural networks) and statistical modeling (linear regression, hypothesis testing).
• Proficiency in Python; familiarity with Apache Spark and big-data tooling is beneficial.
• Experience with model evaluation metrics (F1 score, ROC AUC) and time-series/forecasting techniques.
• Familiarity with Agile/Scrum workflows and rapid prototyping/deployment practices.
• Strong verbal and written communication skills; ability to present complex analyses to business partners.
• Demonstrated teamwork, ability to mentor peers, and willingness to lead research efforts on cross-functional teams.
• Willingness to travel throughout the organization’s service territory and work extended hours as required.

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Benefits & Additional Info

• Competitive compensation and incentive opportunities.
• Retirement plan options (401(k) with employer contribution and company-sponsored pension plan where applicable).
• Medical, prescription drug, dental, vision, and life insurance options.
• Professional development and tuition reimbursement.
• Commitment to workplace safety and a culture that values reliability and operational excellence.
• Workforce diversity is supported; all qualified applicants will receive consideration without regard to protected characteristics.
• Unable to sponsor or transfer H‑1B visas at this time.
• No third-party recruiters or agencies without a previously signed contract.

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.