SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Wealthsimple, Canada's leading financial innovator, is seeking a Senior Data Scientist to join the Growth Data team within the Data Science & Engineering organization. The company serves over 4 million Canadians and manages $155+ billion in assets under administration, offering managed investing, trading, cryptocurrency, tax filing, and spending/saving products.
The Growth Data team drives new user acquisition and net deposit targets through paid, organic, and branding marketing initiatives. The team is organized around key domains: promotions, referral and social sharing, paid marketing, and organic/upper funnel marketing measurement.
In this role, you will serve as the Directly Responsible Individual (DRI) for a key marketing pillar, building data products and analytics solutions that directly impact business outcomes. You'll work on sophisticated challenges including marketing optimization algorithms, attribution modeling, experimentation, and strategic measurement. This is a full-stack data science position requiring you to act as an algorithm developer, measurement strategist, analyst, experimenter, and business partner.
Key responsibilities include:
- Building data products and algorithms to optimize marketing performance across budget allocation, targeting, and campaign optimization
- Designing and implementing measurement strategies including attribution modeling, incrementality analysis, and multi-touch attribution
- Driving marketing strategy through data insights, A/B testing, and causal inference to maximize ROI
- Developing and maintaining analytics pipelines and data infrastructure with data engineers
- Conducting exploratory analysis to identify growth opportunities and optimize marketing tactics
- Providing business-as-usual analytics support including reporting, dashboards, and ad-hoc analysis
- Leveraging AI tooling to handle operational tasks and focus on high-impact strategic work
- Partnering with ad platforms (Google, Meta) and internal engineering teams on tracking and measurement
- Taking ownership of projects end-to-end with pragmatic, effective solutions
The role offers high visibility and impact—your work directly influences millions of dollars in marketing spend and Wealthsimple's growth strategy. You'll develop expertise across measurement, A/B testing, causal inference, machine learning, and algorithm development while owning a key pillar of the company's growth strategy.
Wealthsimple is a remote-first workforce with Canadian offices in Toronto. The company offers top-tier health benefits, group savings with employer match, 20 vacation days, 4 wellness days, unlimited sick/mental health days, 90 days away per year to work outside Canada, and employee resource groups.
REQUIREMENTS:
- Understanding of digital marketing mechanics including attribution, ad platforms, tracking, and conversion optimization
- Experience with lifecycle data and understanding how various customer acquisition and retention channels work together holistically
- Strong technical skills in Python and SQL with ability to write production-quality code
- Proven track record in algorithm development, optimization problems, or building data-driven decision systems
- Strong foundation in causal inference, A/B testing, and experimental design
- Excellent communication skills and ability to translate complex technical concepts for non-technical stakeholders
- Demonstrated ownership as data DRI on complex end-to-end projects with proactive understanding of business context and cross-functional systems
- Full-stack data science experience comfortable with everything from dashboards to sophisticated algorithm development
- Ability to contribute to strategic direction in marketing analytics from day one with minimal ramp-up
- Experience at larger-scale tech companies that develop internal analytics and optimization systems (preferred)
- Ability to adjust quickly to changing priorities and manage complexity in fast-paced growth environment
- Pragmatic approach: knowing when to build sophisticated solutions versus simpler approaches
- Passion for measurement and understanding business drivers, navigating attribution and incrementality complexities
- Willingness to teach, learn, and seek feedback continuously
