Data Analyst

• Bachelor's degree in related field from a four-year college or university with two to four years related experience.
• Strong analytical skills and ability to use descriptive statistics & predictive analytics methods to translate data into business insights.
• Ability to work in an environment where activities and deliverables are dependent on a diverse group of technical and business functional experts.
• Demonstrated ability to leverage AI tools (e.g. Claude, Copilot) to accelerate analytical work, with the judgment to validate outputs and apply them responsibly in a client-facing environment.
• Ability to adjust and adapt to constantly changing business needs & priorities.
• Verifiable skill in following through with project/solutions implementation. Adept at leading solutions implementation from identification of opportunity and determining business case/potential value and ROI to results/ROI follow-through.
• Excellent communication and collaboration skills, with particular focus on promoting analysis and proposing solutions.
• Ability to work quickly and efficiently without direction or supervision for extended periods.
• Advanced/expert skills in the use of Microsoft Office applications.
• Demonstrated ability in creative problem solving and innovative solution development.
• Willing to align to a North American work schedule.
• Willing to work onsite fully or as needed on client/account/business needs.
• Exposure to Python, SQL, Databricks and similar applications.
• Familiarity with machine learning concepts and technologies.
• Knowledge of Six Sigma or similar process improvement methodologies.

Responsibilities:

• Partner with internal teams and clients to understand business strategies, processes, and services within the broader industry and competitive landscape.
• Analyze business challenges to identify high-impact, value-driven opportunities using data insights and feasibility assessments.
• Map and evaluate end-to-end business processes, identifying operational, financial, and technological risks, and proposing quantified mitigation strategies.
• Drive continuous improvement by promoting innovation and implementing data-backed solutions.
• Scope, manage, and document analytical projects, including timelines and deliverables.
• Collaborate with stakeholders to define business problems, conduct data analysis, and deliver actionable, measurable recommendations.
• Implement solutions and track outcomes to ensure value realization and continuous optimization.
• Communicate effectively with stakeholders, providing updates on progress, risks, achievements, and aligning needs across teams.
• Present insights and recommendations to all organizational levels, including executives.
• Develop, manage, and maintain reliable reporting systems to support decision-making and action plans.
• Ensure data integrity and leverage reporting and statistical analysis to generate business insights and validate trends.
• Support operational excellence by analyzing customer interactions (live/recorded calls), identifying improvement opportunities, ensuring compliance, and assessing customer sentiment.
• Identify barriers to resolution and enhance customer experience through process improvements.
• Apply prompt engineering techniques to generate accurate, structured, and actionable outputs from AI tools.
• Integrate AI into analytical workflows to accelerate data interpretation, trend identification, hypothesis generation, and insight development.
• Critically evaluate AI-generated outputs, ensuring accuracy, mitigating bias, and validating results before use in business decisions.
• Design AI-assisted workflows where automation supports repetitive tasks while enabling focus on high-value analysis and client-facing deliverables.
• Collaborate with teams to implement solutions, take ownership of initiatives, and ensure accountability for execution and results

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