Senior Business Data Analyst, Performance Management

LifeLabsToronto, ON
$81,431 - $103,825Hybrid

About The Position

LifeLabs is seeking an experienced and highly skilled Senior Business Data Analyst to join their Performance Management & Insights team. This role is crucial for driving data-informed decision-making across LifeLabs’ national operations. The analyst will be responsible for developing trusted reporting, operational KPIs, self-serve Power BI dashboards, and actionable insights to support business performance. Beyond traditional reporting, the successful candidate will enhance operational analytics capabilities by applying advanced analytics, statistical thinking, forecasting, and automation to identify performance risks, evaluate business outcomes, and support proactive decision-making. This involves close collaboration with operational leaders, Finance, IT, Data Management, and cross-functional partners to translate complex business problems into clear analytical approaches and practical recommendations.

Requirements

  • 5+ years of experience in business intelligence, data analysis, operational reporting, performance management, or a related analytics role.
  • University degree in Business, Economics, Statistics, Computer Science, Data Analytics, Engineering, or a related field.
  • Advanced Power BI experience, including dashboard development, data modelling, DAX, Power Query, and building self-serve reporting solutions.
  • Strong SQL skills, with the ability to extract, join, transform, validate, and analyze data from multiple systems.
  • Working knowledge of Python for data analysis, automation, exploratory analysis, and statistical modelling using libraries such as Pandas, NumPy, Matplotlib, Seaborn, or similar tools.
  • Demonstrated ability to apply statistical concepts such as trend analysis, correlation, regression, variance analysis, hypothesis testing, and confidence intervals to support business decisions.
  • Comfort using AI-enabled tools to improve productivity, accelerate code development, automate repetitive tasks, and enhance analytical workflows.
  • Strong analytical and conceptual thinking skills, with the ability to move beyond data manipulation to meaningful interpretation and actionable recommendations.
  • Ability to communicate complex analysis clearly to non-technical audiences through reports, dashboards, presentations, and executive-level storytelling.
  • Strong attention to detail, with a focus on data quality, validation, documentation, and governance.
  • Demonstrated ability to work independently, manage multiple priorities, and operate in a fast-paced environment.
  • Strong collaboration skills and the ability to work with stakeholders at multiple levels across the organization.

Nice To Haves

  • A Master’s degree is considered an asset.
  • Experience with forecasting, workforce planning, capacity planning, simulation, or predictive modelling is considered a strong asset.
  • Familiarity with basic machine learning concepts such as classification, regression, clustering, decision trees, and model evaluation techniques is an asset.
  • Financial acumen and experience conducting financial or operational performance analysis is an asset.
  • Experience in healthcare, regulated environments, workforce management, or large-scale operations is an asset.

Responsibilities

  • Develop, maintain, and enhance operational reporting capabilities that provide leaders with timely, accurate, and actionable performance insights.
  • Design and build comprehensive Power BI reports, self-serve tools, scorecards, and operational health dashboards for Operations leaders, senior leadership, and executive audiences.
  • Establish, monitor, and evolve critical KPIs that help measure operational performance, business outcomes, productivity, service levels, and the impact of change.
  • Analyze operational, workforce, financial, and performance data to identify trends, risks, root causes, and opportunities for improvement.
  • Apply statistical analysis, forecasting, simulation, and basic predictive modelling techniques to support proactive decision-making and operational planning.
  • Use Python, SQL, Power BI, DAX, M Query, Excel, and AI-enabled tools to automate recurring analysis, improve analytical workflows, and develop scalable insights beyond traditional reporting.
  • Partner with Finance to support budget optimization, monitor performance against plan, and identify opportunities to reduce variance.
  • Collaborate with subject matter experts to extract, cleanse, validate, and analyze complex information from multiple data sources.
  • Support workforce management, capacity planning, and forecasting by using historical data, operational trends, and statistical models to assess staffing needs and service-level risks.
  • Partner with Operations leaders to understand business problems, define analytical requirements, and develop insight products that support better decision-making.
  • Translate complex data and analysis into clear, practical recommendations for non-technical stakeholders.
  • Support continuous improvement initiatives by identifying performance gaps, measuring the impact of interventions, and helping leaders prioritize action.
  • Build a strong understanding of end-to-end business processes across operational departments to ensure analytics are relevant, trusted, and actionable.
  • Work cross-functionally with Finance, IT, Data Management, Decision Sciences, and operational teams to improve data quality, reporting processes, and analytical capabilities.
  • Support data governance practices to ensure operational reports and dashboards are accurate, consistent, standardized, and aligned to internal definitions.
  • Validate data sources, business rules, KPIs, and reporting outputs to ensure business users can trust the information being used for decision-making.
  • Document analytical logic, reporting processes, data definitions, and business rules to support transparency and sustainability.
  • Lead or support change management activities after dashboard and reporting delivery to help business teams adopt, embed, and fully use data in daily decision-making.
  • Provide training, guidance, and support to help stakeholders interpret insights and use analytics tools effectively.

Benefits

  • Competitive coverage for employees and their families to support their overall health and wellness needs, including Extended Health Care, Dental Care, and Life Insurance.
  • Retirement Savings Plan
  • Vacation and Wellness Days
  • Employee & Family Assistance Program
  • Financial planning tools
  • Employee recognition initiatives
  • Professional development and membership reimbursement
  • Access to preferred rates and discount programs, including WorkPerks, Home and Auto Insurance, Costco Membership, etc.
  • Optional health-related benefits.
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