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Manager, Statistics and Data Analytics - Remote Canada

Manager, Statistics and Data Analytics - Remote Canada

ConfidentialMumbai, India
8 days ago
Job type
  • Remote
Job description

Overview

Reporting to the Director of Business Intelligence & Analytics, the Manager, Data Analytics & Statistics sets the benchmark for analytical rigor while building lightweight-but-robust processes and standards. This people-first leader will manage a small team of Analysts focused on advanced analytics, turning complex data into trustworthy insights, forecasts, and decision tools for Finance, Operations, Programs, and Regulatory domains.

To thrive in this role, you're fluent in turning data into decisions : comfortable in Python and SQL; proficient in predictive modeling, statistical inference, time-series, and optimization; and familiar with modern ML / analytics workflows. You bring sharp attention to detail, a commitment to reproducibility and experience working from curated datasets in cloud data warehouses. Equally important, you coach and unblock others, communicate trade-offs with clarity, and collaborate effectively across functions to deliver high-impact, reliable analytical products.

Responsibilities

Standards, methods and governance

  • Define best practices for experimentation, model development, validation, monitoring, and documentation.
  • Champion reproducibility (version control, environments, data lineage) and ethical use of data.
  • Partner with Data Engineering on data readiness, feature availability, and deployment pathways (you influence architecture without owning it).

Project Delivery

  • Scope and prioritize a portfolio of advanced analytics initiatives (e.g., forecasting material flows, optimizing collection logistics, program performance measurement, fraud / anomaly detection).
  • Translate ambiguous business questions into well-framed analytical problems with clear success metrics.
  • Guide end-to-end work : problem definition, exploratory analysis, feature design, model selection / assessment, implementation, and post-launch monitoring.
  • Team leadership & coaching

  • Lead, mentor, and develop a small team of analysts; run effective 1 : 1s, set goals, grow skills, and foster an inclusive, feedback-rich culture.
  • Establish code review norms, analytical playbooks, and reusable templates that raise quality and speed.
  • Stakeholder Engagement

  • Communicate findings with clarity tailoring depth for executives, program owners, and technical peers.
  • Facilitate decisions through scenario modeling, sensitivity analysis, and trade-off discussions.
  • Quality, impact and enablement

  • Build metrics to track the business value and reliability of analytical assets.
  • Create onboarding materials and workshops to upskill analysts and data consumers across the organization.
  • Qualifications

    Education

  • Post secondary education / Bachelor's degree in a relevant field such as Computer Science, Mathematics, Engineering, Economics, or Finance.
  • An advanced degree (Masters or above) in Business, Mathematics, Analytics or Statistics is an asset.
  • An equivalent combination of education, and experiences may be considered.
  • AWS Certifications, Certified Data Scientist is an asset.
  • Experience

  • 6+ years of progressive analytics experience with demonstrated leadership of small teams (formal people management or strong tech-lead experience).
  • Proven record delivering advanced analytical solutions that informed operations, policy, or strategy.
  • Strong proficiency in Python for analytical development; SQL for data wrangling and performance-aware querying.
  • Hands-on experience with predictive modeling, statistical inference, and optimization (e.g., regression, classification, time-series, causal methods, linear / nonlinear optimization).
  • Familiarity with modern ML / analytics workflows : feature engineering, model validation, cross-validation, drift / monitoring, experiment design (A / B or quasi-experimental).
  • Comfort with version control (Git), notebooks and modular code, and documenting analyses for reproducibility.
  • Experience working with cloud data warehouses (e.g., AWS Redshift) and orchestrating analyses from curated datasets.
  • Prior working experience in the recycling industry, regulated / reporting‑heavy environments (EPR, utilities, public sector, finance) is an asset.
  • Agile and sprint development experience is an asset.
  • Knowledge / Competencies / Skills

  • Excellent communicator who can simplify complexity, align stakeholders, and influence decisions with evidence.
  • Product mindset : starts with the decision / use-case, defines success metrics, and ships incrementally to learn.
  • Meticulous attention to detail with structured critical thinking; balances statistical rigor with auditability and practical decisions.
  • Comfortable working in ambiguous, high-pressure environments, with a proven ability to multi-task, prioritize, and coordinate resources effectively.
  • Thoughtful people leader who coaches, unblocks, and elevates others; sets crisp expectations and gives timely, actionable feedback.
  • WORKING CONDITIONS

  • All CM employees work 40 hours per week, remotely from a home office environment.
  • About Circular Materials

    Circular Materials is a national not-for-profit producer responsibility organization (PRO) that supports producers in meeting their extended producer responsibility (EPR) obligations across Canada. Created by producers for producers, Circular Materials develops, implements, and supports effective and efficient recycling programs to advance innovation, deliver improved environmental outcomes and drive value across the recycling supply chain. Our full-service offerings include collection, management, promotion and education, and reporting.

    Together, we are advancing the circular economy where materials are collected, recycled, and can be returned to producers for use as recycled content in new products and packaging. As we develop enhanced recycling systems across Canada, we work to ensure more materials are looped into the circular economy, benefiting both people and the environment.

    Learn more at circularmaterials.ca.

    Circular Materials is an equal opportunity employer, seeking team members with a diversity of thought, skills, experiences, culture, and ethnicity to help us achieve our purpose of accelerating a circular economy for people and the planet. As a national organization operating across Canada, our goal is to build a workforce that reflects the diversity of the many provinces and territories where we do business.

    Our Inclusive Hiring Practices Aim To Foster a Culture Where All Employees Feel a Strong Sense Of Belonging. We Are Proud Of Our Recent Diversity Survey Results Which Showed That

  • 51% of Circular Materials employees identify as women.
  • 53% of Circular Materials employees identify as visible minorities.
  • 97% of employees believe Circular Materials fosters a strong sense of belonging for employees of all backgrounds.
  • 95% of employees recommend Circular Materials as an inclusive workplace.
  • We welcome applications from candidates of all backgrounds, including women, Indigenous Peoples (First Nations, Inuit, and Métis), persons with disabilities, racialized individuals, and members of the 2SLGBTQIA+ community. As part of our commitment to reconciliation, Circular Materials is working to advance Indigenous representation and partnerships within our organization and across our programs. We acknowledge that Circular Materials operates on the traditional territories of diverse Indigenous Nations, and we recognize the importance of respecting Indigenous rights, governance, and contributions in the workplace and beyond.

    Circular Materials supports reasonable requests for accommodation in accordance with all applicable provincial accessibility standards. Requests for accommodation will be provided by Circular Materials through the recruitment and / or assessment processes, upon contacting [HIDDEN TEXT]. This email is only used for accommodation requests.

    Skills Required

    Statistical Inference, Predictive Modeling, Optimization, Sql, Python

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