Quantitative Analytics Lead

Affirm; Oshawa; Remote; CAD 142,000 - 192,000; Full time

Job summary

A leading company is seeking a Quantitative Analytics Lead to join their dynamic team. This role involves enhancing analytical tools for predicting loan performance and requires expertise in quantitative methodologies. If you have a strong analytics background and wish to work cross-functionally to drive insights, this position is tailored for you.

Benefits

Health care coverage

Flexible Spending Wallets

Competitive vacation and holiday schedules

Employee stock purchase plan

Qualifications

• Strong analytical and problem solving skills.
• Solid knowledge of analytical tools.
• Experience with quantitative research methodologies and machine learning algorithms.

Responsibilities

• Develop and refine analytical tools for modeling loan performance.
• Collaborate with Machine Learning and Engineering teams.
• Conduct code review for team members' implementations.

Skills

Analytical skills

Problem solving

Interpersonal skills

Curiosity

Education

Undergraduate, Masters, or PhD in Computer Science or related field

Tools

GitHub

Job description

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Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.

We’re looking for an intelligent, driven professional to join our Quantitative Research team. Quantitative Research is a part of the broader Quantitative Markets team, which is responsible for structuring and pricing Affirm’s debt funding deals and researching and building data-driven models to analyze and predict the performance of Affirm’s consumer loans.

In this role, you will be primarily focused on analytical tools development, working with engineers and data scientists around the company to improve the usability of the take-up and loan cashflow models. Over time, you would proactively engage with other stakeholders around Affirm to tailor models to the needs of Merchant Pricing, Credit, Applied Machine Learning, Finance, and other stakeholders.The ideal candidate will have strong analytical and problem solving skills with solid knowledge of analytical tools, as well as interpersonal skills to work cross-functionally and drive forward recommendations.

This is an individual contributor position.

What you’ll do

• Architect, build, refine and increase automation and research infrastructure for modeling the performance of existing collateral and simulation frameworks for future loan originations
• Collaborate with platform (Machine Learning and Engineering) teams to implement framework for automating and presenting analytics, reports, and monitoring
• Collaborate with firm-wide analytics teams to deliver analyses and tools to users across the firm
• Review implementation of models focusing on requirement verification and code quality. Conduct code review for different members of the team.
  
  

What we look for

• Undergraduate, Masters, or PhD in Computer Science or other quantitative discipline
• 4-7 years of professional experience developing quantitative infrastructure tools and platforms
• Solid background in math/statistics/finance and familiarity with quantitative research methodologies and machine learning algorithms
• Analyze unique business operational requirements and conduct research in order to design appropriate technical solutions to accommodate those functional needs
• Ability to contribute to the analytics, research, and model development process
• Curiosity to learn about data, models and algorithms and proven track record in analytical and problem solving skills
• Ability to develop strong relationships and work across all organizational levels
• Desire to understand the broader context of business decisions
• Github experience preferred. Existing github presence a plus
  
  

Pay Grade - Q

Equity Grade - 7

Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.

Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)

CAN base pay range per year: $142000 - $192000

Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.

Benefits

We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:

• Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents
• Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
• Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge
• ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount
  
  

We believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.

By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Research, Analyst, and Information Technology

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