{"id":3532217,"url":"https://alion.io/job/exl-lead-data-analyst","title":"Lead Data Analyst","company":{"id":38016,"name":"EXL","domain":"exlservice.com","url":"https://alion.io/company/exl","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":75,"open_postings":236,"ghost_share":0,"stale_share":0.987,"repost_share":0,"time_to_fill_p50_days":27,"computed_at":"2026-11-03T05:54:40Z"}},"role":"Analytics","role_family":"Analytics","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":62000,"max_usd":110000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":27},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":true},{"name":"Databricks","optional":true},{"name":"GDPR","optional":true},{"name":"Looker","optional":true},{"name":"NumPy","optional":true},{"name":"Pandas","optional":true},{"name":"Power BI","optional":true},{"name":"Python","optional":true},{"name":"Snowflake","optional":true},{"name":"SQL","optional":true},{"name":"Tableau","optional":true},{"name":"Time Series","optional":true}],"status":"live","first_seen_at":"2026-10-30T14:33:27Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-03T04:24:21Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Lead Data Analyst\nRemote; Canada\n$90k-130k plus annual bonus\nFor more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits\nThe 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.\nEXL 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.\nThe 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.\nResponsibilities\nStakeholder Partnership & Communication\nAct as the main analytics point of contact for marketing, international and regional stakeholders, building trusted working relationships across the client organization.\n\nTranslate ambiguous business questions into clearly scoped analysis with agreed objectives, success measures and timelines.\n\nPresent findings and recommendations to senior stakeholders, tailoring the level of detail to the audience and leading the discussion that follows.\n\nWrite 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.\n\nManage expectations on scope, priorities and delivery dates, and keep stakeholders informed as work progresses.\n\nTeam Leadership & Mentorship\nServe as the senior analyst on the team: set analytical standards, review other analysts’ work and give constructive, practical feedback.\n\nMentor and coach junior and mid-level analysts on technical skills, business context and stakeholder communication.\n\nPrioritize and coordinate incoming analytics requests across the team, allocating work and unblocking colleagues.\n\nBuild and maintain documentation, reusable code and shared definitions so the team’s work is consistent and repeatable.\n\nHands-on Analysis\nWrite efficient SQL and Python to extract, clean, transform and analyze large fan and marketing datasets.\n\nWork within cloud data platforms (Databricks, Snowflake, AWS) to build and maintain analytical datasets and workflows.\n\nDevelop audience segments and test/control designs that support 1:1 marketing campaigns and deepen fan engagement.\n\nSummarize large data outputs into clear, business-friendly takeaways.\n\nReporting, Advanced Analytics & Data Quality\nOwn the recurring reporting on fan growth, engagement and lifecycle metrics across international markets.\n\nMonitor campaign and go-to-market (GTM) performance against agreed KPIs and success criteria, and recommend where to optimize.\n\nDevelop and maintain advanced analytics models, such as segmentation, propensity, churn and customer lifetime value, and translate their output into recommendations stakeholders can act on.\n\nBuild and maintain forecasts of fan growth, engagement and campaign performance to support planning and target setting across international markets.\n\nMeasure and validate model and forecast accuracy over time, and refine the approach as markets and data evolve.\n\nSupport user acceptance testing (UAT) of database changes and help data engineering teams with root cause analysis (RCA) of data issues.\n\nWork with data engineering on business requirements, and liaise with third-party partners on data needs and definitions.\n\nRequired Qualifications\nBachelor’s degree in Analytics, Computer Science, Statistics, Economics, Business or a related field, or equivalent experience.\n\n5-7 years of experience in a data analyst or similar role, including experience working directly with business stakeholders.\n\nDemonstrated ability to present analysis to senior, non-technical audiences and influence decisions.\n\nExperience mentoring, coaching or reviewing the work of other analysts.\n\nStrong SQL skills, including complex joins, aggregations and window functions.\n\nProficiency in Python for data analysis (e.g., pandas, NumPy).\n\nHands-on experience with at least one cloud data platform: Databricks, AWS or Snowflake.\n\nExperience building advanced analytics models and forecasts (e.g., segmentation, propensity, churn, time series) and applying them to business decisions.\n\nStrong analytical and problem-solving skills, with close attention to detail.\n\nPreferred Qualifications\nExperience with BI and visualization tools (e.g., Tableau, Power BI, Looker).\n\nExperience in marketing, CRM or customer analytics.\n\nKnowledge of consent management, identity resolution or privacy regulations such as PIPEDA and GDPR.\n\nExperience in a consulting or client-facing environment.\n\nPassion for sport and an understanding of global fan cultures.\n\nResponsibilities:\nIdentify and shape analytics opportunities with league and club stakeholders\nBuild trusted relationships with club and league stakeholders and understand their strategic priorities, business challenges, and opportunities.\n\nProactively identify areas where data and analytics can help clubs grow their fan base, increase revenue, and deepen fan engagement.\n\nTranslate business problems into well-defined analytics opportunities, hypotheses, and use cases\n\nHelp prioritize opportunities based on business impact, data availability, scalability, and feasibility\n\nTranslate business needs into analytics solutions\nPartner with data scientists and analysts to translate business questions into analytical requirements, hypotheses, and solutions.\n\nDefine analytical approaches, success metrics, required data, and expected business outcomes.\n\nEnsure analytics products and models are designed with the end user and business decision in mind.\n\nPerform hands-on analytics and develop actionable insights\nUse SQL extensively to extract, transform, analyze, and validate data.\n\nPerform exploratory and diagnostic analysis to uncover trends, patterns, opportunities, and business drivers.\n\nWork with large and complex datasets and combine information from multiple data sources.\n\nUse Python/Pandas and other analytical tools for deeper analysis, modeling, and visualization where appropriate.\n\nTurn analytical findings into clear, practical recommendations that clubs can act upon\n\nMaintain technical depth to independently investigate data, validate analyses, and contribute directly to analytical deliverables.\n\nCommunicate with stakeholders and support delivery\nPresent complex analytical concepts and findings in a simple, compelling, business-oriented manner.\n\nBuild executive-ready presentations and narratives that connect data to business outcomes.\n\nReview analytical approaches, outputs, and recommendations to ensure quality and business relevance\n\nRequired Skills\n5+ years of experience in analytics, business strategy, consulting, or a related field, with meaningful experience working directly with a professional sports club/team or league.\n\nDemonstrated experience working directly with business stakeholders to identify and solve business problems.\n\nStrong business acumen with the ability to understand business objectives and translate them into analytics opportunities\n\nStrong SQL skills and hands-on experience working with large datasets.\n\nExperience with Python/Pandas or a similar analytics programming language Strong presentation, storytelling, and stakeholder management skills.\n\nAbility to operate independently 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