Manager – Reporting and Analysis

Req 4357

The return on your career investment

• Compensation and incentives built to reward the value you bring.
• RRSP matching of up to 6%.
• Health and wellness resources and programs, including $5,000 in mental health practitioner coverage.
• $5,000 in tuition subsidies for job-related courses, every year.
• 100% parental top-up, up to 26 weeks for birthing parents and 18 weeks for non-birthing parents.
• A hybrid environment, with at least three days in the office built for working together.
• Paid vacation, personal, and sick days.
• A community care day to give back to the causes you care about.

This job posting is for an existing vacancy. 

We’re looking for our next Senior Manager, Data Science & Service Intelligence

The Sr. Manager, Data Science & Service Intelligence is accountable for rebuilding how Sales & Service leverages data, predictive models, and conversational AI to drive operational decisions. Operating as a hands-on player-coach, this role leads the transformation of reporting into predictive service intelligence, establishing governed metrics in BigQuery and Power BI while connecting telephony, CRM, and cloud warehouse ecosystems. The role partners cross-functionally with Workforce Management, Product, Technology, and operational leadership to isolate root causes of friction and measurably elevate client experience across channels

The Mandate

In this role, responsibilities include but are not limited to: 

• Establishing and owning the metric framework for Sales & Service as a single source of truth, building governed data models in Google BigQuery and self-serve Power BI dashboards while retiring redundant legacy reporting and enforcing data quality and lineage standards.
• Architecting and maintaining reliable data pipelines and API integrations across Genesys Cloud, Salesforce, Google BigQuery, and internal platforms, breaking down operational silos in collaboration with central Data and Technology teams.
• Personally developing predictive models, statistical forecasts (e.g., volume, handle time, attrition risk), and controlled experimentation pilots using Python and advanced SQL, providing the analytical modeling engine for Workforce Management and operational planning.
• Owning the end-to-end measurement framework for conversational AI across voice and chat (containment, resolution accuracy, escalation behavior, unit cost), analyzing conversation transcripts at scale to uncover failure points and steer model improvements with automation teams.
• Interrogating contact patterns, escalation trends, and client feedback to quantify root causes of friction in volume and cost, delivering prioritized, evidence-backed business cases to Product and Technology to permanently eliminate recurring issues.
• Formulating and tracking outcome-focused KPIs (centering on First Contact Resolution) for specialist pods, equipping frontline leaders with diagnostic coaching insights that measurably enhance operational performance and client experience.
•  Directing, mentoring, and elevating a team of analysts through disciplined technical standards and modern development workflows (including prompt engineering and LLM-assisted workflows), driving organizational scale through automation and technology rather than headcount.
• Partnering across Sales & Service, Operations, Product, Technology, and external vendors, translating complex data findings into actionable executive narratives, trade-off evaluations, and strategic business decisions.
  
  

You’re ready for this mandate if you have the following qualifications

• Have a Bachelor's degree in a quantitative or technical field (Statistics, Mathematics, Computer Science, Engineering, Economics, or related discipline), or equivalent practical experience.
• Have 5+ years of experience in analytics, data science, or a related quantitative technical field, including at least 2 years directly leading, mentoring, or guiding the technical work of analysts.
• Have advanced SQL proficiency querying cloud data warehouses (e.g., Google BigQuery) and working proficiency in Python or R for statistical analysis and predictive modeling.
• Have hands-on experience integrating multi-source operational data (telephony, CRM, data warehouses), creating data pipelines/APIs, and developing enterprise-grade business intelligence reporting (e.g., Power BI).
• Have a demonstrated track record taking a predictive model, statistical forecast, or experiment from initial concept to active business implementation that directly influenced operational decisions.

Nice to have

• Have applied experience measuring, tuning, or evaluating conversational AI / virtual agent systems across chat and voice channels.
• Have prior domain experience in contact centers, operations, or a regulated financial services/brokerage environment.
• Have hands-on familiarity with Genesys Cloud and Salesforce operational data models.
• Have experience with analytics engineering practices and tooling (e.g., dbt, data transformation modeling, orchestration)

Enter your career inflection point. Apply now.

#LI-Hybrid

#LI-DB1

Base salary range 120000 - 140000 CAD