Digital Data Product Analyst bridging business stakeholders, analytics teams, and data management at EXL. Delivering insights, requirements, and reliable data products for sports, fan, and business use cases.
About the role
- Senior Data Product Analyst shaping and evaluating data-driven products combining analytics and product development at Guideline. Focusing on transforming complex datasets into actionable insights for marketing decisions.
Responsibilities
- Partner with Product and Engineering teams to research, evaluate, and develop new data-driven products and feature enhancements, conducting deep analyses on complex spend, pricing, and performance datasets to identify patterns, assess data viability, and inform design decisions from concept through production.
- Contribute to go-to-market release execution by validating data in production environments, coordinating QA and feature testing, preparing product collateral, and delivering internal demos to align stakeholders on new functionality — all to drive successful adoption and launch readiness.
- Support release management by validating production data, investigating anomalies, providing analytical context for product and customer teams, and coordinating release communications to facilitate transparency and smooth deployment across teams.
- Design and implement automated data validation and quality frameworks for digital products — defining thresholds, conditional formatting, and anomaly detection logic to proactively flag and resolve data issues, streamline QA processes, and ensure accuracy and reliability across releases.
- Lead critical business-as-usual operations for monthly data releases, ensuring quality, reliability, and on-time delivery for customers by driving validation efforts, coordinating stakeholders, and resolving issues efficiently to support client retention and confidence.
- Champion best practices in data governance, validation, and experimentation, establishing standards and documentation that enhance data quality, reliability, and analytical rigor across teams.
- Play an active role in PI Planning, shaping backlog priorities, validating scope and acceptance criteria, and ensuring coordination across Product and Engineering teams to set realistic and value-driven delivery goals.
- Leverage AI-powered analytical tools and LLM-based workflows to accelerate data validation, insight generation, and documentation.
- Partner with engineering teams to integrate machine-learning–based anomaly detection and data quality checks into the product pipeline.
- Identify product opportunities where AI or predictive modeling can enhance user experience, improve accuracy, or surface actionable insights.
- Evaluate dataset readiness for AI/ML use cases, ensuring structures, definitions, and data governance support high-quality model performance.
Requirements
- Extensive experience as a Data Analyst in a data-centric or product-driven environment, with the ability to translate analytical insights into product strategy and measurable business impact.
- Strong analytical and problem-solving skills — able to identify trends, anomalies, and opportunities in large datasets.
- Proficiency in SQL for querying, transforming, and validating complex datasets.
- Hands-on experience with Power BI or equivalent BI tools (Tableau, Looker, Sisense, Qlik).
- Demonstrated ability to communicate complex findings clearly, collaborate effectively with cross-functional teams, and influence decisions across Product, Engineering, and Operations.
- Highly organized, detail-oriented, and proactive in managing multiple priorities and deadlines.
Benefits
- Health, dental, life, and disability insurance
- RRSP with company match
- Paid time off and parental leave
- Teledoc Health services
- Employee recognition and referral bonuses
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