Director of Data

Director of Data at Mercury

In the 1970s, engineer Ezdgar Codd proposed a radical idea: instead of the hierarchical databases his employer IBM used and sold, he proposed the concept of “relational databases” to manage large datasets. His ideas, codified with a set of rules called Codd's 12 rules, fundamentally transformed how we store, retrieve, manipulate, and manage data, enabling advancements across various sectors of society and industry.

We’re looking for a Director of Data who can help us use the approaches that led to the creation of relational databases to drive Mercury’s success.

About the Role

In this role, you’ll be responsible for a team of 30+ data scientists and data engineers embedded across product teams and will be a critical role to inform how we invest in and build Mercury’s future. You’ll be early to building a data-informed culture across Mercury so that we can all determine what's happening, react quickly, and invest intelligently.

Key Responsibilities

• Build, manage, and develop a team of 15+ data scientists across Growth, Risk, Core Product and business expansion to help Mercury make better decisions informed by data.
• Influence data analytics and data engineering culture and rigor across different levels, from executives to individual product and operations teams. This will range from product analytics for our core products, to advanced statistical methods for risk and credit underwriting.
• Guide the strategy, architecture, and tooling of Mercury’s data infrastructure to enable the entire company to use data effectively.

What You'll Bring

• Have 10+ years of experience, including 4+ years managing a team of data science or data engineering managers.
• Be able to partner with business leaders, GMs, and Executives to ensure that they and their teams have the tools, reporting, and support to consistently make the best data-informed decisions. Proactively provide advanced analytics and insights to leaders that they may not be seeing.
• Be opinionated on the ways to most effectively use data to make decisions.
• Strong knowledge and hands-on experience with data science, machine learning, statistics, financial calculations, and experimentation for commercial applications.
• Create an inspiring and empowered work environment for data scientists and data engineers to thrive, including defining clear career paths and identifying individual growth opportunities.
• Have experience working with People, Legal, Compliance, and Privacy teams to ensure that we are enforcing best practices and compliant standards for data privacy and security.

Compensation & Benefits

The total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits.

Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following:

• US employees: $320,000-$400,000
• Canadian employees (any location): CAD $302,400-$378,000

Diversity & Inclusion

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

Recruitment Process Note

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on January 22, 2024.

[Please see the independent bias audit report covering our use of Covey for more information.]

Key skills/competency

• Data Science
• Data Engineering
• Machine Learning
• Statistical Modeling
• Product Analytics
• Data Strategy
• Leadership
• Team Management
• Data Infrastructure
• Fintech