Lead Data Analyst

Lead Data Analyst

Remote; Canada

$90k-130k plus annual bonus

For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits

The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.

EXL is looking for a Lead Data Analyst with a passion for sports who will play a key role in providing analytics support to a client within our Sports, Media and Entertainment practice. Based in Toronto, the role sits within the International Fan Data & Analytics team, supporting fanbase growth and engagement across international markets.

The ideal candidate brings 5–7 years of analytics experience, excellent communication and stakeholder management skills, and a strong understanding of the fan lifecycle. You are comfortable working through ambiguity, confident presenting to audiences who are not technical, and motivated by helping the analysts around you do their best work.

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.