Data Scientist, Link
On-siteToronto, Ontario, Canada
Toronto, Ontario, CanadaOn-siteFull TimeDoctorate Or Professional DegreeFintechLarge
Full TimeDoctorate Or Professional DegreeLargeFintech
Job Summary
Drive local payment method enablement and consumer feature optimization for Stripe's Link team by running experiments, analyzing friction points, and synthesizing complex analyses into actionable recommendations. Leverage causal inference, machine learning, and statistical modeling to optimize systems, forecast outcomes, and shape consumer payment preferences across global markets. Collaborate with cross-functional teams to deliver results on product analytics and growth initiatives while deploying models in production to improve performance.
Required Qualifications
- PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience
- 3+ years in Product Analytics, Experimentation and Causal Inference
- Experience designing, running, and analyzing complex experiments or leveraging causal inference designs
- Proficiency in SQL and Python
- Experience in working with cross-functional teams to deliver results
- Ability to communicate results clearly and a focus on driving impact
- A demonstrated ability to manage and deliver on multiple projects with a high attention to detail
- Strong business acumen and experience in synthesizing complex analyses into actionable recommendations
- Proficiency with AI tools to accelerate model development, analysis, and coding
Desired Qualifications
- Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation
- Experience deploying models in production and adjusting model thresholds to improve performance
- A builder's mindset with a willingness to question assumptions and conventional wisdom
- Experience with distributed tools such as Spark, Hadoop, etc.
- A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)
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