Senior Data Scientist, Applied AI

Engineering at Brex

The Engineering team includes Data, IT, Security, and Software, and is responsible for building innovative products and infrastructure for both internal and external users. We have multiple autonomous and collaborative teams who are eager to learn, teach, and constantly improve how things work. Together, we strive to build robust and scalable systems that enable Brex to grow rapidly and help our customers reach their full potential.

Applied AI at Brex

As part of Brex’s AI team, Applied AI leverages cutting-edge AI/ML techniques to empower automation solutions in Brex’s spend management offering, working closely with Product, Design, and Engineering teams. 

What you’ll do

The Applied AI team drives for a more streamlined experience for our customers via AI/ML automations. We are looking for a strong Data Scientist to join our nimble and effective team. You will be responsible for the full cycle of work from ideation, research, and development to production and further improvements, working both strategically and tactically with cross-functional stakeholders to balance priority and delivery. 

Responsibilities

• Design and implement spend management related solutions with ML and AI techniques 
• Partner closely with Product Managers, Designers, and Engineers to understand their needs and identify opportunities to accelerate the AI/ML development and deployment process
• Consult and educate internal teams on current and up-and-coming research, technologies, and best practices of leveraging ML and LLM in product design and development 
• Work closely with AI Platform engineers to identify upcoming requirements and continuously evolve the AI platform offering 

Requirements

• 4+ years of industry experience developing optimization models that drive business impact
• Passion for delivering data-driven solutions leveraging data, ML, and AI
• M.S. or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field
• Familiarity with programming languages (e.g. Python) and machine learning libraries (e.g. SciKit Learn)
• Deep understanding of natural language processing techniques 
• Experience in overall big data analysis and system-backed integration with ML/LLM system/solution
• Good understanding of quantitative disciplines such as statistics, machine learning, operations research, and causal inference
• Experience productionizing and A/B testing different machine learning models
• Must be willing to work in office 2 days per week on Wednesday and Thursday

Bonus points

• Experience leveraging commercial or open source LLM APIs to build solutions, such as OpenAI or llama 
• Experience in the finance industry

Compensation

The expected salary range for this role is $176,800 CAD - $221,000 CAD. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.