Bread is a technology company that aims to transform the way the world shops online. We build tools, technologies and APIs that allow e-commerce merchants to integrate installment loan financing and other alternative payment products anywhere in their customers’ shopping journey. Bread was started in 2014 by financial technology veterans, and has experienced explosive growth to date. We’re backed by top investors including Menlo Ventures, Bessemer Venture Partners, Kinnevik, among others.

Are you passionate about data? Are you someone who prides yourself on your ability to use data to shape decisions around business strategy, product design, and profitability? The Analytics team at Bread is tasked with navigating and understanding Bread’s vast first and third party data and works closely with management stakeholders across Product, Finance, Engineering, and other departments to ensure that we are making the best data-backed decisions we possibly can. As a key member of our growing team, you will report directly to our Lead Analyst and work on some of the most exciting, cross-functional projects at Bread. This role will involve: modeling new products and growth opportunities, deep-dive research into consumer conversion and repayment behavior, and revenue and profitability reporting among other responsibilities. You will be the “data expert” in the room and a key partner to every business team at Bread. This will involve both ‘teaching them to fish’ through coaching, reporting, and self-service tools, as well as ‘fishing’ by providing your own analysis and insights. This will originally be an individual contributor role, however, there may be opportunities to manage other analysts as the team grows.

Your role at Bread:

• Prioritization: Supporting company leadership, including the C-suite, to identify the highest ROI projects. 

• A/B Testing: You’ll work with our product teams to design, set-up, monitor, and assess changes to our platform via A/B testing, analyzing the conversion effects across the funnel. You’ll be a part of the process from start to finish, from brainstorming new ways to improve conversion and profitability to calculating the final results to inform the roll-out decision.
• Statistical Analysis and Predictive Modeling: From helping Finance understand changes in YoY loan performance to attribution across our merchant portfolio, you’ll help answer ad-hoc questions and add to our knowledge base. This involves writing complex SQL queries to bring our internal and external data together and applying statistical modeling techniques such as linear regression, logistic regression, time series analysis, and even data science techniques where appropriate.
• Data Modeling and Data Warehousing: As we add new features to our platform or start tracking new data points, you’ll work with the engineering team to incorporate these new data points into our data infrastructure and load them into our data warehouse.

• Learning and Teaching: As our team grows, we’ll continue to contribute to a company-wide data-first culture and team-wide culture of continuous learning and improvement. You’ll be asked to share discoveries, refine our problem discovery process, and shape our processes and infrastructure.

What we are looking for:

Must Have:

• 3-5 years of experience in analytical roles or engineering (software engineering, data engineering) roles
• Professional experience in mentorship and/or leadership roles
• BA in a quantitative field: Stats, Finance, Economics, Math, or Computer Sciences
• Fluency in SQL and at least one functional programming language, especially Python or R
• Expert knowledge of statistics, i.e. confidence intervals, linear regression, and hypothesis testing
• Experience with funnels and event tracking software, i.e. Heap or Mixpanel
• Effective interpersonal skills

Nice to Have:

• Experience with any technologies in our analytics stack: Snowflake, PostgreSQL, DBT, Databricks and/or Spark, Airflow, Python, Github, Looker, and Docker  
• Experience in financial services or credit
• Experience with web applications
• Familiarity with other languages in our technology stack: Golang and Javascript
• An advanced degree
• Familiarity with survey data, software, and methods 
• Familiarity with an agile working environment