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Data Analyst Lmia Jobs (NOW HIRING)

... CEO | LMIA / PNP sponsorship available About the Client Our client is one of Canada's fastest ... This is a builder role for a Risk Leader with hacker instincts and raw analytical horsepower ...

... CEO | LMIA / PNP sponsorship available About the Client Our client is one of Canada's fastest ... This is a builder role for a Risk Leader with hacker instincts and raw analytical horsepower ...

Analyze sales and KPI data to improve performance * Oversee scheduling to align with business needs ... LMIA) that would support a foreign worker. Applications will not be accepted via email or in person.

Data Analyst Lmia information

See salary details

$34K

$82.6K

$136K

How much do data analyst lmia jobs pay per year?

As of Jun 10, 2026, the average yearly pay for data analyst lmia in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What is the difference between Data Analyst Lmia vs Data Scientist?

AspectData Analyst LmiaData Scientist
Required CredentialsBachelor's degree in related field, certifications like Microsoft Excel, SQLBachelor's or higher in CS, stats, or related; often advanced certifications or degrees
Work EnvironmentOffice settings, data analysis teams, client-facing rolesResearch labs, tech companies, data-driven departments
Employer & Industry UsageBusiness, finance, healthcare, governmentTech, finance, e-commerce, research institutions
Common Search & ComparisonYesYes

While both roles involve working with data, Data Analyst Lmia focuses on interpreting and visualizing data to support business decisions, often requiring certifications like SQL and Excel. Data Scientists typically handle complex models and algorithms, requiring advanced degrees. The roles overlap in industry and work environment but differ in technical depth and responsibilities.

What are the key skills and qualifications needed to thrive as a Data Analyst (LMIA), and why are they important?

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or related fields. Familiarity with data analysis tools like SQL, Excel, Python, Tableau, and sometimes certifications such as Microsoft Certified Data Analyst are commonly expected. Attention to detail, problem-solving ability, and effective communication skills help you translate complex data into actionable insights for stakeholders. These skills are crucial for interpreting data accurately and supporting business decisions that drive organizational success.

What is a Data Analyst LMIA?

A Data Analyst LMIA refers to a Data Analyst position that requires a Labour Market Impact Assessment (LMIA) in Canada. An LMIA is a document that employers in Canada may need to obtain before hiring a foreign worker, proving that no Canadian citizen or permanent resident is available to fill the job. Data Analysts in LMIA-approved roles are responsible for collecting, processing, and analyzing data to help organizations make informed decisions. These positions often require strong analytical skills, proficiency in statistical tools, and the ability to communicate findings effectively. Being LMIA-approved can help a foreign Data Analyst obtain a work permit to legally work in Canada.
Infographic showing various Data Analyst Lmia job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Hybrid job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Lead Risk Manager, Payment Fraud

Worthland

New York, NY • Hybrid

$150K - $180K/yr

Full-time

Posted 3 days ago


Job description

Lead Risk Manager, Payment Fraud

Toronto Onsite | Full-Time | Hybrid after onboarding | Reports to CEO | LMIA / PNP sponsorship available

About the Client

Our client is one of Canada's fastest-growing fintech platforms, transforming how consumers pay, save, and earn rewards through a single seamless app. The company processes over USD $100M in annual transaction volume (TPV) with a base of 250,000+ users across North America, and its proprietary, fully in-house technology stack supports 500+ leading retail and brand partners. Headquartered in the Greater Toronto Area with a growing presence in Silicon Valley, the company is currently scaling at 300% year-over-year and is expanding its financial product suite into new categories.

Role Overview

Risk management at this company is not a brake on growth — it is the engine that powers it. The Lead Risk Manager will own end-to-end fraud and payment risk strategy across a multi-currency, cross-border consumer payments ecosystem, building AI-driven detection systems that automate over 90% of fraud interception and free the team from manual review cycles.

This is a builder role for a Risk Leader with hacker instincts and raw analytical horsepower — someone who can reverse-engineer fraud loops, write production-grade SQL and Python, and deploy ML models (XGBoost, LightGBM) into live risk systems. The role reports directly to the CEO and operates as the strategic liaison to global payment processors and vendors.

Key Responsibilities

Define the rules, don't just follow them — Lead end-to-end financial risk strategies, from opportunity identification through design, testing, and post-production monitoring.

Build AI-driven defense — Develop user behaviour scoring, anomaly detection, and automated interception models using Python/Sklearn/XGBoost/LightGBM, and deploy them into the production risk stack.

Counter-strike fraud — Investigate anomalous activity in real time, perform root-cause analysis on chargebacks, and produce authoritative reports on emerging fraud trends across multi-currency and e-commerce flows.

Own the data layer — Independently query large datasets in SQL to surface fraud patterns, evaluate model performance, and inform strategy adjustments.

Strategic liaison — Act as the single point of contact between the company and external payment processors, card networks, and risk vendors, ensuring alignment on risk policy and incident response.

Set the standard — Establish the company's long-term risk operating framework as the platform scales TPV and enters new markets.

Must-Have Requirements

• 5+ years of professional experience, with a minimum of 3 years dedicated to fraud risk and at least 1 year specifically within the payments industry.

• Hands-on experience identifying and defending against fraud across multi-currency, cross-border, and e-commerce payment environments.

• Strong reverse-engineering and problem-solving instincts — able to anticipate attacks from a fraudster's perspective.

• Expert-level SQL for independent querying of large transactional datasets; strong Python proficiency.

• 3+ years of hands-on experience building fraud detection models — feature engineering, training, evaluation, and production deployment.

• Demonstrated proficiency with Python/R modeling frameworks: Sklearn, XGBoost, LightGBM.

• Mandarin Chinese fluency (the company operates a bilingual EN/CN working environment; this is a hard requirement).

• Based in or willing to relocate to the Greater Toronto Area for the onsite onboarding period.

Nice to Have

• Prior experience at a top-tier payment processor, card network, or fintech with cross-border exposure.

• Experience leading or mentoring a small risk / data team.

• Familiarity with North American AML/KYC and consumer payment compliance frameworks.

Compensation & Logistics

Base Salary: CAD 150K to 180k

Bonus: Risk control performance bonus tied to fraud loss reduction and model deployment milestones.

Work Model: Hybrid in Toronto, with a paid 1–2 month onsite onboarding period at the Etobicoke office.

Reporting Line: Direct report to the CEO.

Immigration Support: Full LMIA and PNP employer sponsorship for top-tier candidates, including all associated costs.

Team: Work alongside payment industry veterans and a Harvard-affiliated founder defining the future of AI-driven financial security.

Why This Role

This is not a maintenance seat at a stagnant company. It is a builder seat at a Canadian fintech in hyper-growth, with direct CEO access, a real budget for AI tooling, and the autonomy to define the risk operating model from the ground up. For a senior risk professional who wants to operate as a general rather than an analyst, this is one of the most consequential fraud roles open in the Canadian market today.