Technical APM, Analytics and ML
Toronto
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingWork hands-on with analytics and data systems to monitor data fidelity, diagnose pipeline issues, and improve performance
Collaborate daily with engineering, data science, and ML teams to design, scope, and ship customer-facing analytics and ML products
Work with integration partners across major platforms (e.g., Google, Meta, Amazon, Reddit)
From the employer’s posting
Analytics, Data & ML Enablement Work hands-on with analytics and data systems to monitor data fidelity, diagnose pipeline issues, and improve performance Leverage SQL, Python, and modern analytics tools to explore client data, build metrics, and support experimentation (e.g., incrementality testing, predictive modeling)
Product Development & Roadmap Influence Collaborate daily with engineering, data science, and ML teams to design, scope, and ship customer-facing analytics and ML products Contribute directly to the analytics and ML product roadmap, informed by customer discovery and usage patterns
Cross-Functional & Strategic Impact Work with integration partners across major platforms (e.g., Google, Meta, Amazon, Reddit) Synthesize complex technical and business information into actionable recommendations for leadership
Tools in this posting
- Python
- SQL
- BigQuery
- Looker
Source — Tool mentions in context
- Work hands-on with analytics and data systems to monitor data fidelity, diagnose pipeline issues, and improve performance - Leverage SQL, Python, and modern analytics tools to explore client data, build metrics, and support experimentation (e.g., incrementality testing, predictive modeling) - Support and contribute to the AI training lifecycle, including data preparation, feature validation, and performance monitoring
- 1–2 years of experience in analytics, data science, or machine learning - Strong analytical foundation with exposure to SQL, Python, data analysis, or ML concepts - Comfort working with technical systems and collaborating closely with engineers and data scientists
Technical & Analytical Skills - Working knowledge of SQL and data modeling concepts - Familiarity with analytics and data platforms (e.g., BigQuery, Looker/Looker Studio, or similar)
- Working knowledge of SQL and data modeling concepts - Familiarity with analytics and data platforms (e.g., BigQuery, Looker/Looker Studio, or similar) - Exposure to machine learning concepts, experimentation frameworks, or predictive analytics
Benefits in the posting
Full benefits wording- Market-competitive compensation based on experience
- Meaningful equity in a fast-growing AI startup
From the employer’s posting.
Job description
What You’ll Do
Analytics, Data & ML Enablement
- Work hands-on with analytics and data systems to monitor data fidelity, diagnose pipeline issues, and improve performance
- Leverage SQL, Python, and modern analytics tools to explore client data, build metrics, and support experimentation (e.g., incrementality testing, predictive modeling)
- Support and contribute to the AI training lifecycle, including data preparation, feature validation, and performance monitoring
- Help shape ML-powered features, automation, and predictive insights that improve customer outcomes
Product Development & Roadmap Influence
- Collaborate daily with engineering, data science, and ML teams to design, scope, and ship customer-facing analytics and ML products
- Contribute directly to the analytics and ML product roadmap, informed by customer discovery and usage patterns
- Identify opportunities to standardize, automate, and scale analytics workflows across customers
- Help define product documentation, playbooks, internal tooling, and best practices
Cross-Functional & Strategic Impact
- Synthesize complex technical and business information into actionable recommendations for leadership
What We’re Looking For
Core Qualifications
- 1–2 years of experience in analytics, data science, or machine learning
- Strong analytical foundation with exposure to SQL, Python, data analysis, or ML concepts
- Comfort working with technical systems and collaborating closely with engineers and data scientists
- Ability to explain complex technical concepts to non-technical stakeholders
- Strong ownership mindset, curiosity, and bias toward action
Technical & Analytical Skills
- Working knowledge of SQL and data modeling concepts
- Familiarity with analytics and data platforms (e.g., BigQuery, Looker/Looker Studio, or similar)
- Exposure to machine learning concepts, experimentation frameworks, or predictive analytics
- Ability to reason about data pipelines, data quality, and system performance (without needing to be a full-time engineer)
Bonus Experience
Location
Compensation & Benefits
- Market-competitive compensation based on experience
- Meaningful equity in a fast-growing AI startup
- Flexible, remote-first work environment
- Structured mentorship and career development
- Team events, offsites, and collaborative culture
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Toronto
- Meaningful equity in a fast-growing AI startup - Flexible, remote-first work environment - Structured mentorship and career development
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Jun 2, 2026
- Recorded sightings
- 42
- Last seen by us
- Sep 29, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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