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Financial Data Analyst | Nuclear

  • Oshawa, ON, Canada

Contract

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Job details

Job type
Contract
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Positions available
2
Posting language
English
Posted

Original job description

We are currently requesting resumes for the following position: Financial Data Analyst

Resume Due Date: Monday November 2nd, 2026 (5:00PM EST)

Number of Vacancies: 2

Level: MP5

Contract Duration: 24 months

Hours of work: 40 per week

Location: 1908 Colonel Sam, Drive Oshawa | Hybrid 2 days onsite 3 days remote

We are seeking a Finance Data Analyst to support data-driven decision-making across the finance function. In this role, you will analyze financial and operational data, develop reports and dashboards, identify trends and performance drivers, and deliver actionable insights to stakeholders. You will work closely with finance and business teams to improve reporting, streamline processes, and support planning, forecasting, and performance management activities.

Key Responsibilities

  • Partner with finance stakeholders to understand reporting and analysis needs
  • Collect, clean, validate, and analyze financial and business data from multiple sources
  • Build and maintain dashboards, reports, and visualizations to support decision-making
  • Identify trends, anomalies, risks, and opportunities in financial performance
  • Support budgeting, forecasting, variance analysis, and management reporting
  • Help improve data quality, consistency, and reporting processes
  • Translate data into clear insights and recommendations for non-technical stakeholders
  • Collaborate with data, finance, and business teams to improve access to trusted data
  • Support ad hoc analysis and presentation materials for leadership

Qualifications

  • Bachelor's degree in Finance, Accounting, Economics, Data Analytics, Statistics, Business, or a related field
  • Experience in data analysis, business analysis, or finance analytics
  • Strong proficiency in Excel and SQL
  • Experience with visualization and reporting tools such as Power BI or Tableau
  • Strong analytical, problem-solving, and communication skills
  • Ability to present findings clearly to business stakeholders
  • Finance or accounting knowledge is preferred

Preferred Skills

  • Experience with Python or R for analysis is a plus
  • Familiarity with financial reporting, planning, and performance metrics
  • Understanding of data quality, governance, and process improvement
  • Experience working with large datasets and multiple business systems
  • Knowledge in SAP S4, SAP ECC, SAP SAC/BDC, Anaplan
More about this job

Responsibilities

Analyze financial and operational data, develop reports and dashboards, and identify trends, risks, and performance drivers. Support budgeting, forecasting, variance analysis, and management reporting while improving data quality and communicating actionable insights to stakeholders.

Requirements

A bachelor's degree in finance, accounting, economics, data analytics, statistics, business, or a related field is specified, along with experience in data, business, or finance analytics. Strong Excel and SQL skills, experience with Power BI or Tableau, and analytical, problem-solving, and communication abilities are required; finance knowledge is preferred.

Skills

  • Financial Data Analysis
  • Excel
  • SQL
  • Power BI
  • Tableau
  • Financial Reporting
  • Budgeting
  • Forecasting
  • Variance Analysis
  • Dashboard Development
  • Data Visualization
  • Data Quality
  • Stakeholder Communication
  • Python
  • R
  • SAP

Visa sponsorship

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Categories

  • Finance & Accounting
  • Data & Analytics
  • Energy

Keywords

  • Financial Data Analysis
  • Financial Data
  • Operational Data
  • Excel
  • SQL
  • Power BI
  • Tableau
  • Python
  • R
  • SAP S4
  • SAP ECC
  • SAP SAC/BDC
  • Anaplan
  • Financial Reporting
  • Budgeting
  • Forecasting
  • Variance Analysis
  • Management Reporting
  • Performance Metrics
  • Dashboard Development
  • Data Visualization
  • Data Quality
  • Data Governance
  • Process Improvement
  • Stakeholder Communication
  • Large Datasets
  • Ad Hoc Analysis

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