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Data Scientist - Job Opportunity at ShyftLabs

Toronto, Canada
Full-time
Senior
Posted: April 17, 2025
Hybrid
CAD 120,000 - 160,000 annually based on Toronto market rates for senior data scientists with ML specialization

Benefits

Competitive healthcare insurance package with comprehensive coverage
Professional development resources and learning opportunities
Flexible hybrid work arrangement (2 days office presence)
Work-life balance focused environment

Key Responsibilities

Lead complex data analysis and ML system optimization initiatives to drive performance improvements and cost efficiencies
Design and execute advanced simulation models to validate system performance hypotheses
Develop experimental frameworks and metrics for product decision-making
Drive data-driven insights for Fortune 500 client solutions

Requirements

Education

Master's degree in a quantitative discipline or equivalent

Experience

5+ years minimum professional experience

Required Skills

Advanced statistical analysis and experimental design Machine learning algorithm expertise (deep learning, random forest, gradient boosted trees, k-means clustering) Python, R, or other scripting languages SQL and data manipulation Cross-functional collaboration Problem-solving Communication skills
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Sauge AI Market Intelligence

Industry Trends

Growing demand for ML optimization specialists as companies focus on efficiency and cost reduction in their AI systems Increased emphasis on experimental design and causal inference skills in data science roles Rise of hybrid roles combining ML engineering and traditional data science

Role Significance

Likely part of a specialized data science team of 5-8 members, working closely with ML engineers and product teams
Senior individual contributor role with significant technical decision-making authority and direct impact on product performance

Key Projects

ML system optimization and cost efficiency initiatives Experimental design and metric framework development Large-scale data analysis and insight generation for enterprise clients

Success Factors

Deep understanding of both theoretical and practical aspects of ML systems Ability to translate complex technical concepts into business value Strong experimental design and causal inference expertise Excellent stakeholder management skills

Market Demand

High demand with strong growth trajectory, particularly in the enterprise solutions sector working with Fortune 500 clients

Important Skills

Critical Skills

ML System Optimization: Essential for core role responsibilities and product performance Experimental Design: Critical for validation and decision-making processes Statistical Analysis: Fundamental for data-driven insights and recommendations

Beneficial Skills

Cloud Infrastructure Knowledge: Helpful for understanding system architecture Business Analytics: Valuable for stakeholder communication Project Management: Useful for coordinating cross-functional initiatives

Unique Aspects

Rare combination of ML system optimization and business impact focus
Direct work with Fortune 500 clients despite being a younger company
Strong emphasis on scientific rigor in approach to product improvement

Career Growth

2-3 years in role before advancement opportunities, depending on project impact and leadership development

Potential Next Roles

Lead Data Scientist ML Engineering Manager Technical Product Manager Data Science Architect

Company Overview

ShyftLabs

Early-stage data product company founded in 2020, focusing on enterprise digital solutions

Growing presence in the enterprise solutions sector with Fortune 500 client base
Toronto-based with potential for expanding influence in North American market
Innovation-focused environment with emphasis on professional growth and work-life balance
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