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Added 11 mins ago
TB
Senior DevOps Engineer (SRE / Platform Engineering)
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Vancouver, BC
- Full-time
Support cloud infrastructure, platform management, system deployments and production operations.
Added 11 mins ago
CH
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- Full-time
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Added 11 mins ago
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Added 11 mins ago
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Added 11 mins ago
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Support the development and improvement of aircraft cabin acoustic and vibration performance.
Added 11 mins ago
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Added 11 mins ago
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Added 11 mins ago
ZS
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Toronto, ON
- Full-time
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Added 11 mins ago
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Added 11 mins ago
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Added 11 mins ago
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Added 26 mins ago
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Added 26 mins ago
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Added 26 mins ago
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NerdWallet

Senior Data Scientist (Applied ML) - Canada

Remote, Canada

Remote

$161,000 to $243,000 CAD / year · Full-time

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Job details

Pay: $161,000 to $243,000 CAD / year
Job type: Full-time
Workplace: Remote
Posting language: English
Posted: Nov 4, 2026

Original job description

At NerdWallet, our mission is to provide clarity for all of life's financial decisions. Data Science plays a critical role in delivering on that mission, helping us better understand our consumers, personalize their experiences, and connect them with the financial products that best meet their needs.

We’re growing, and we’re looking for a Senior Data Scientist (Applied ML) to join us as a foundational member of our new team. You’ll help shape and advance our machine learning capabilities across consumer personalization, predictive modeling, and performance marketing, with a real voice in how we work from day one. Together, we’re building an inclusive, supportive team culture where we lift each other up and succeed together to drive business impact across the organization.

In this role, you will lead the development of production-grade machine learning solutions that power some of NerdWallet's most critical business decisions. From predicting customer lifetime value and scoring incoming leads in real time to developing recommendation engines that connect consumers with the right financial products, your work will have a direct impact on how we acquire, engage, and monetize our customer relationships.

This is a hands-on individual contributor role for someone with deep expertise in applied machine learning, production ML systems, and the Databricks ecosystem. As a foundational member of the team, you’ll partner closely with Data Engineering, Product, Marketing, and Analytics to translate complex business problems into scalable ML solutions, while helping establish the technical standards and best practices for machine learning across NerdWallet.

Where you can make an impact:

Build Predictive Models That Drive Business Growth

Lead the end-to-end development of advanced machine learning models focused on customer lifetime value (LTV), conversion propensity, lead quality, and revenue optimization.
Translate model predictions into actionable signals that improve marketing investment decisions, customer acquisition efficiency, and long-term profitability.

Advance Personalization & Recommendation Systems

Develop recommendation and ranking models that identify the most relevant financial products for individual consumers based on their needs, behaviors, and predicted propensity to engage or convert.
Explore and implement approaches such as propensity modeling, learning-to-rank, and next-best-product recommendations to improve customer engagement and cross-sell opportunities.
Collaborate with Product and Marketing to integrate predictive intelligence into consumer experiences and personalized communications.

Establish Best-in-Class ML Practices

Leverage Databricks and MLflow to develop, train, deploy, monitor, and manage machine learning models at scale.
Establish robust DS practices, including experiment tracking, model versioning, feature engineering, automated training pipelines, model monitoring, and reproducibility.
Define standards for model performance, reliability, retraining, and production readiness, including monitoring for data drift and model degradation.
Design and evaluate experiments to measure the incremental business impact of deployed models and continuously improve their effectiveness.
Serve as a technical leader within Data Science, mentoring other practitioners, influencing architectural decisions, and elevating engineering and modeling standards across the organization.

Your experience:

5+ years of professional experience in Data Science, Applied Machine Learning, or a related field, with a demonstrated track record of developing and deploying ML solutions that drive measurable business impact.
Deep, hands-on experience with Databricks, including building and managing production machine learning workflows using MLflow and the Databricks ML ecosystem. Please note: this role requires hands-on Databricks experience specifically, and experience with similar platforms is not a substitute.
Advanced proficiency in Python and SQL, with extensive experience using modern machine learning frameworks such as scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow.
Strong understanding of supervised learning, predictive modeling, classification, regression, ranking, and model evaluation techniques.
Practical experience designing scalable batch and/or real-time inference systems, with an understanding of latency, reliability, and performance trade-offs.
Strong software engineering fundamentals, including version control, testing, modular code design, and CI/CD practices for machine learning.
Demonstrated ability to independently lead complex, ambiguous technical initiatives from problem definition through deployment and business impact measurement.
Strong business acumen and the ability to connect technical solutions to measurable outcomes such as revenue growth, conversion improvement, customer lifetime value, and marketing efficiency.
Excellent communication and collaboration skills, with experience influencing technical direction and working effectively with senior stakeholders and cross-functional teams.
Bachelor's or advanced degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative discipline, or equivalent practical experience.

Where:

This is a remote position and a person can be located anywhere in Canada (with the exception of Quebec).
NerdWallet is proud to be a remote-first company! We believe great work can be done anywhere. No matter where you are based, NerdWallet offers benefits and perks to support the physical, financial, and emotional well being of you and your family.

What we offer:

Work Hard, Stay Balanced (Life’s a series of balancing acts, eh?)

Monthly Healthcare Stipend
Rejuvenation Policy – Vacation Time Off + You will receive the official public holidays in your province
Paid sabbatical for Nerds to recharge, gain knowledge and pursue their interests
Monthly Wellness Stipend, Wifi Stipend, and Cell Phone Stipend
Work from home equipment stipend

Have Some Fun! (Nerds are fun, too)

Nerd-led group initiatives – Employee Resource Groups for Parents, Diversity, and Inclusion, Women, LGBTQIA, and other communities
Hackathons and team events across all teams and departments
Company-wide events like NerdLove (employee appreciation) and our annual Charity Auction

Plan for your future (And when you retire on your island, remember the little people)

RRSP with a 4% match. Eligible one month after hire.
Financial wellness, guidance, and unlimited access to a Certified Financial Planner (CFP) through Northstar

NerdWallet is committed to pursuing and hiring a diverse workforce and is proud to be an equal opportunity employer. We prohibit discrimination and harassment on the basis of any characteristic protected by applicable federal, state, or local law, so all qualified applicants will receive consideration for employment.

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More about this job

Responsibilities

Lead the development and deployment of production-grade machine learning models for customer lifetime value, conversion propensity, lead quality, revenue optimization, and personalized product recommendations. Establish scalable ML practices using Databricks and MLflow, measure business impact through experiments, and provide technical leadership across Data Science and partner teams.

Requirements

Requires at least five years of relevant professional experience, hands-on production ML experience with Databricks and MLflow, and advanced Python and SQL skills. Candidates should have strong modeling and software engineering fundamentals, experience with scalable inference systems, and the ability to lead ambiguous initiatives and connect technical work to business outcomes; a relevant bachelor's or advanced degree, or equivalent practical experience, is required.

Skills

Applied Machine Learning
Databricks
MLflow
Python
SQL
Predictive Modeling
Supervised Learning
Classification
Regression
Learning-To-Rank
Recommendation Systems
Feature Engineering
Model Evaluation
Real-Time Inference
CI/CD
Experiment Design

Benefits

Monthly Healthcare Stipend
Vacation Time Off
Provincial Public Holidays
Paid Sabbatical
Monthly Wellness Stipend
Wi-Fi Stipend
Cell Phone Stipend
Work-From-Home Equipment Stipend
Employee Resource Groups
Hackathons And Team Events
Company-Wide Events
RRSP With 4% Match
Financial Wellness Guidance
Unlimited Access To A Certified Financial Planner

Remote locations

Canada

Remote locations (standardized)

Canada

Visa sponsorship

Not detected in the job text

Keywords

Databricks
MLflow
Python
SQL
Scikit-Learn
XGBoost
LightGBM
PyTorch
TensorFlow
Applied Machine Learning
Predictive Modeling
Customer Lifetime Value
Conversion Propensity
Lead Scoring
Recommendation Systems
Learning-To-Rank
Feature Engineering
Automated Training Pipelines
Model Monitoring
Data Drift
Model Versioning
Experiment Tracking
Batch Inference
Real-Time Inference
CI/CD
Supervised Learning
Classification
Regression
Marketing Optimization

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