Data Science Analyst

• Develop validate and deploy statistical and machine learning models to improve forecasting accuracy across revenue and expense categories in a complex Utilities & Energy business environment.
• Build driverbased and predictive forecasting models to support annual planning rolling forecasts and longrange planning with an accountable focus on measurable improvement.
• Perform model validation backtesting and error analysis to continuously improve performance and ensure trusted decisionready outputs.
• Translate analytical results into clear financial narratives and actionable recommendations for FP&A leadership and business partners demonstrating strong business acumen and customer focus.

• Champion data integrity by supporting initiatives that improve the quality consistency and reliability of financial and operational datasets.
• Define and apply data validation reconciliation and control frameworks across key FP&A data flows to ensure accuracy and accountability.
• Collaborate closely with IT and Data Engineering partners to ensure accurate integration of ERP planning and operational systems; clear data lineage; and standardized definitions that enable a single source of truth.
• Proactively identify and remediate data issues that impact forecasting reporting and downstream decisionmaking in an agile and solutionoriented manner.

• Conduct deepdive analyses to uncover trends risks opportunities and key business drivers that inform strategic and operational decisions.
• Deliver executiveready insights visualizations and storytelling that enable leaders to act with confidence.
• Design maintain and evolve standardized KPIs and metrics frameworks aligned to business objectives and customer outcomes.
• Enable selfservice analytics by creating curated datasets reusable logic and scalable analytical solutions that drive innovation and continuous improvement.

• Bachelors degree in Data Science Statistics Finance Accounting Economics Computer Science or a related field.
• 3 years of experience in data analytics data science or FP&A with demonstrated exposure to advanced analytics or predictive modeling.
• Strong proficiency in Python and/or R for statistical analysis and machine learning in a business context.
• Strong proficiency in SQL for data extraction transformation validation and quality assurance.
• Experience building evaluating and interpreting predictive or statistical models that support realworld business decisions.
• Working knowledge of forecasting concepts financial drivers and data governance principles with a strong data integrity mindset.
• Ability to clearly and authentically communicate complex analytical concepts to nontechnical stakeholders and senior leaders.

• Experience in FP&A corporate finance or financial analytics within a large matrixed organization.
• Familiarity with enterprise financial systems such as Oracle ERP/EPM SAP or similar platforms.
• Experience working with modern data platforms such as Microsoft Fabric Snowflake Databricks or comparable technologies.
• Experience using Power BI or other business intelligence tools to deliver clear customercentric visualizations and insights.
• Exposure to model lifecycle concepts including deployment monitoring and continuous improvement.
• Experience operating in large multisource data environments demonstrating collaboration agility and innovation.

The successful candidates starting salary will be determined based on permissible non-discriminatory factors such as skills and experience and may vary by location. The base salary is $ annually.

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