Senior Manager, Data Science & Analytics

Overview

This is a senior leadership opportunity for a data science and analytics professional based in Canada. The role sits at the crossroads of analytics, strategy, and business impact, with responsibility for turning large, complex datasets into practical insights that guide product choices, customer experience improvements, marketing optimization, and revenue expansion.

You will lead a team that works in a fast-moving, analytics-led environment and collaborate with senior stakeholders across several functions to define success metrics, develop forecasting and behavioral models, and strengthen experimentation practices. The position combines people leadership with deep hands-on analytical work, and it is well suited to someone who is comfortable navigating ambiguity while translating data into clear decisions. You will also help advance modern analytics capabilities such as self-serve data access and scalable measurement infrastructure.

This opportunity is intended to shape how data influences decisions inside a rapidly growing, product-led organization.

Accountabilities

• Guide, coach, and grow a team of Data Scientists and Analysts supporting multiple business areas.
• Lead initiatives in behavioral analysis, customer segmentation, experimentation, and product performance tracking.
• Create and sustain forecasting models, churn prediction models, customer health scoring, and revenue or opportunity models.
• Work closely with teams in Product, Marketing, Sales, and Customer Experience to help set priorities and influence business direction.
• Partner with data engineering to improve internal analytics systems and support scalable self-service reporting and analysis.
• Establish consistent standards, frameworks, and practices that improve quality, rigor, and efficiency across analytics delivery.

Requirements

• At least 7 years of experience in Data Science, Product Analytics, Business Analytics, or another quantitative discipline.
• Demonstrated success in leading and developing strong analytics or data science teams.
• Deep knowledge of experimentation design, statistical methods, forecasting, and behavioral analytics.
• Advanced SQL capability along with strong Python skills or experience with similar analytical programming tools.
• Proven ability to design measurement frameworks and support data-driven decisions in product or growth-focused settings.
• Strong communication skills with the ability to present complex findings clearly to both technical audiences and senior business leaders.
• Practical experience with modern data environments such as Snowflake, dbt, and product analytics platforms.
• Background in B2B SaaS, product-led growth, or subscription-based businesses is highly desirable.

Benefits

• Competitive annual base pay between USD 170,000 and USD 200,000, depending on experience.
• Full coverage for medical, dental, vision, mental health, and supplemental insurance for employees and their families.
• 16 weeks of fully paid parental leave.
• Unlimited paid time off.
• Remote-first work setup with a globally distributed team.
• Yearly allowances for home office setup, wellness, and professional growth.
• Strong commitment to learning, advancement, and career development.
• An inclusive, people-centered culture grounded in transparency, empathy, and accountability.

Application process and data notice

This role is listed on behalf of a partner employer, which handles applications and all subsequent hiring steps directly. Applications are reviewed through an AI-supported matching process designed to evaluate fit against the role’s core requirements in a fair and objective way. The strongest matches are forwarded to the hiring company, while interviews, assessments, and the final decision are managed by their internal team.

By applying, candidates acknowledge that personal data will be processed to assess candidacy and shared with the hiring employer where relevant. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws, including GDPR. Candidates may request access, correction, deletion, or objection at any time.

AI tools may be used to assist with parts of the recruitment workflow, such as screening applications, reviewing resumes, analyzing responses, or flagging potential inconsistencies in submitted information. These tools support the recruitment team and do not replace human judgment. Final hiring decisions are made by people.

Interested candidates are encouraged to apply through the application process provided for this opportunity.