Data Scientist II Core AIML

Burnaby - Canada

Monthly Salary: Not Disclosed

Posted on: 22 hours ago

Vacancies: 1 Vacancy

Job Summary

Job Description:

About the Role

At Remitly we are on a mission to transform lives by providing trusted financial services that transcend borders. We serve millions of customers sending billions of dollars each year across 170 countries and our work impacts communities on a truly global scale.

As a Data Scientist at Remitly you will contribute to data-driven decision-making across product and business domains. Data Scientists work hand-in-hand with Machine Learning Engineers and partner closely with Product Analytics and Engineering to shape AI/ML products through rigorous analytics experimentation and modeling. We work horizontally across domains at Remitly including Global Money Movement Treasury Identity & Trust Promotions Referrals and more.

We are looking for a Data Scientist who can independently execute well-scoped analysis and modeling work apply sound statistical reasoning and clearly communicate insights while continuing to grow depth in causal thinking and applied modeling.

What Youll Do

Execute the end-to-end lifecycle of data science projects for well-defined problems including exploratory data analysis modeling evaluation and communication of results.
Partner with Machine Learning Engineers to support production models through offline analysis feature and label exploration evaluation metrics and monitoring insights.
Contribute to estimating opportunity size and expected impact for AI and data initiatives to help inform prioritization.
Apply standard experimentation and causal analysis techniques to measure impact with guidance on more complex designs.
Design analyze and interpret A/B tests including metric selection bias checks and interpretation of results.
Translate analytical findings into clear actionable insights for product and business partners.
Build and maintain reproducible analytical workflows and datasets that support reliable experimentation and decision-making.
Participate in analysis and design reviews incorporating feedback to improve analytical quality and rigor.

What You Bring

Degree in Data Science Statistics Mathematics Economics Computer Science or equivalent practical experience.
2 years of industry experience in data science analytics applied statistics or a related field.
Strong proficiency in SQL and working proficiency in Python with the ability to write clear reproducible data analysis code.
Solid understanding of experimentation and statistical analysis including hypothesis testing confidence intervals and metric interpretation.
Experience working with messy real-world data to uncover meaningful insights.
Experience collaborating cross-functionally with Product Engineering or Machine Learning partners.
Ability to communicate clearly with both technical and non technical audiences explaining results assumptions and limitations.
Exposure to causal inference forecasting or optimization techniques is a plus.

Remitly is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Required Experience:

Job Description:About the RoleAt Remitly we are on a mission to transform lives by providing trusted financial services that transcend borders. We serve millions of customers sending billions of dollars each year across 170 countries and our work impacts communities on a truly global scale.As a Data...

Job Description:

About the Role

What Youll Do

Execute the end-to-end lifecycle of data science projects for well-defined problems including exploratory data analysis modeling evaluation and communication of results.
Partner with Machine Learning Engineers to support production models through offline analysis feature and label exploration evaluation metrics and monitoring insights.
Contribute to estimating opportunity size and expected impact for AI and data initiatives to help inform prioritization.
Apply standard experimentation and causal analysis techniques to measure impact with guidance on more complex designs.
Design analyze and interpret A/B tests including metric selection bias checks and interpretation of results.
Translate analytical findings into clear actionable insights for product and business partners.
Build and maintain reproducible analytical workflows and datasets that support reliable experimentation and decision-making.
Participate in analysis and design reviews incorporating feedback to improve analytical quality and rigor.

What You Bring

Degree in Data Science Statistics Mathematics Economics Computer Science or equivalent practical experience.
2 years of industry experience in data science analytics applied statistics or a related field.
Strong proficiency in SQL and working proficiency in Python with the ability to write clear reproducible data analysis code.
Solid understanding of experimentation and statistical analysis including hypothesis testing confidence intervals and metric interpretation.
Experience working with messy real-world data to uncover meaningful insights.
Experience collaborating cross-functionally with Product Engineering or Machine Learning partners.
Ability to communicate clearly with both technical and non technical audiences explaining results assumptions and limitations.
Exposure to causal inference forecasting or optimization techniques is a plus.