Responsibilities
Stakeholder Partnership & Communication
Act as the main analytics point of contact for marketing, international and regional stakeholders, building trusted working relationships across the client organization.
Translate ambiguous business questions into clearly scoped analysis with agreed objectives, success measures and timelines.
Present findings and recommendations to senior stakeholders, tailoring the level of detail to the audience and leading the discussion that follows.
Write clear summaries and narratives that make complex analysis easy to act on, and challenge or reframe requests where the data points to a better question.
Manage expectations on scope, priorities and delivery dates, and keep stakeholders informed as work progresses.
Team Leadership & Mentorship
Serve as the senior analyst on the team: set analytical standards, review other analysts’ work and give constructive, practical feedback.
Mentor and coach junior and mid-level analysts on technical skills, business context and stakeholder communication.
Prioritize and coordinate incoming analytics requests across the team, allocating work and unblocking colleagues.
Build and maintain documentation, reusable code and shared definitions so the team’s work is consistent and repeatable.
Hands-on Analysis
Write efficient SQL and Python to extract, clean, transform and analyze large fan and marketing datasets.
Work within cloud data platforms (Databricks, Snowflake, AWS) to build and maintain analytical datasets and workflows.
Develop audience segments and test/control designs that support 1:1 marketing campaigns and deepen fan engagement.
Summarize large data outputs into clear, business-friendly takeaways.
Reporting, Advanced Analytics & Data Quality
Own the recurring reporting on fan growth, engagement and lifecycle metrics across international markets.
Monitor campaign and go-to-market (GTM) performance against agreed KPIs and success criteria, and recommend where to optimize.
Develop and maintain advanced analytics models, such as segmentation, propensity, churn and customer lifetime value, and translate their output into recommendations stakeholders can act on.
Build and maintain forecasts of fan growth, engagement and campaign performance to support planning and target setting across international markets.
Measure and validate model and forecast accuracy over time, and refine the approach as markets and data evolve.
Support user acceptance testing (UAT) of database changes and help data engineering teams with root cause analysis (RCA) of data issues.
Work with data engineering on business requirements, and liaise with third-party partners on data needs and definitions.
Required Qualifications
Bachelor’s degree in Analytics, Computer Science, Statistics, Economics, Business or a related field, or equivalent experience.
5–7 years of experience in a data analyst or similar role, including experience working directly with business stakeholders.
Demonstrated ability to present analysis to senior, non-technical audiences and influence decisions.
Experience mentoring, coaching or reviewing the work of other analysts.
Strong SQL skills, including complex joins, aggregations and window functions.
Proficiency in Python for data analysis (e.g., pandas, NumPy).
Hands-on experience with at least one cloud data platform: Databricks, AWS or Snowflake.
Experience building advanced analytics models and forecasts (e.g., segmentation, propensity, churn, time series) and applying them to business decisions.
Strong analytical and problem-solving skills, with close attention to detail.
Preferred Qualifications
Experience with BI and visualization tools (e.g., Tableau, Power BI, Looker).
Experience in marketing, CRM or customer analytics.
Knowledge of consent management, identity resolution or privacy regulations such as PIPEDA and GDPR.
Experience in a consulting or client-facing environment.
Passion for sport and an understanding of global fan cultures.
