Senior Data Scientist - Cards and Credit
In the 1950s, Norman Borlaug embarked on an effort to breed a new type of wheat that was disease resistant and had higher yields. In the outskirts of Mexico City, he combined his background of agricultural research and theoretical knowledge with careful experimentation and diligent data collection to run over 6,000 experiments - and he was ultimately successful, kicking off the “Green Revolution” that increased global crop yields by an estimated 44% and earned him a Nobel Prize.
At Mercury, we’re building the future of financial infrastructure for startups and growing businesses. We’re looking for a full-stack Data Scientist to support our Cards & Credit roadmap, partnering closely with Product, Engineering, Design, Underwriting, and Operations to shape how our card and credit products evolve and scale.
In this role, you’ll apply strong analytical judgment and product intuition to help us understand customer behavior, evaluate tradeoffs, and make smart investment decisions across the cards and lending lifecycles — from eligibility and activation to spend, retention, incentives, and credit performance. You’ll help build a data-informed culture across Mercury so teams can move quickly, measure what matters, and invest intelligently.
Here are some things you’ll do on the job:
Bring impeccable communication and complete ownership — independently identifying opportunities, developing strong points of view, and influencing executives, Cards & Credit leaders, and cross-functional partners through clear, concise, and persuasive storytelling.
Develop a nuanced understanding of cardholder behavior and economics, helping teams reason about tradeoffs between growth, engagement, risk, and unit economics.
Define, own, and analyze metrics that inform both tactical decisions and long-term strategy across the cards and credit lifecycle (e.g., eligibility, activation, spend, utilization, rewards, retention, loss signals).
Design and evaluate experiments using rigorous statistical approaches, including A/B testing, cohort analysis, causal inference techniques, and trend analysis.
Build and improve data pipelines and tools to streamline data collection, processing, and analysis workflows, ensuring the integrity, reliability, and security of data assets.
You should:
Bring 7+ years of experience working with large datasets to drive product or business impact in data science or analytics roles.
Be fluent in SQL and comfortable with python.
Demonstrate strong judgment in defining and analyzing product metrics, running experiments, and translating ambiguous questions into structured analyses.
Operate with exceptional proactivity and independence — identifying opportunities, forming strong points of view, and making your case to stakeholders.
Be experienced with modern analytics and data modeling stacks (e.g., dbt, dimensional models), with a solid understanding of how data is produced and consumed.
Apply AI tools to accelerate analytical and business workflows, improving scalability, decision quality, and reducing manual or repetitive work across teams.
Nice to have:
Experience working on cards or credit products, such as corporate cards, charge cards, consumer cards, or revolving credit products.
Familiarity with card economics and lifecycle concepts, including spend behavior, interchange, rewards and incentives, utilization, credit limits, and retention.
Experience leveraging underwriting inputs, lifecycle risk signals, or third-party credit data to inform or optimize credit strategy or product decisions.
Experience building or supporting credit models for cards or lending products, including probability of default modeling, credit limit setting, or portfolio monitoring.
The total rewards package at Mercury includes base salary, equity (stock options), 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 (any location): $200,700 - $250,900 USD
Canadian employees (any location): CAD 189,700 - 237,100
Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.
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.
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.]
#LI-RA1
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Senior Data Scientist - Cards and Credit
In the 1950s, Norman Borlaug embarked on an effort to breed a new type of wheat that was disease resistant and had higher yields. In the outskirts of Mexico City, he combined his background of agricultural research and theoretical knowledge with careful experimentation and diligent data collection to run over 6,000 experiments - and he was ultimately successful, kicking off the “Green Revolution” that increased global crop yields by an estimated 44% and earned him a Nobel Prize.
At Mercury, we’re building the future of financial infrastructure for startups and growing businesses. We’re looking for a full-stack Data Scientist to support our Cards & Credit roadmap, partnering closely with Product, Engineering, Design, Underwriting, and Operations to shape how our card and credit products evolve and scale.
In this role, you’ll apply strong analytical judgment and product intuition to help us understand customer behavior, evaluate tradeoffs, and make smart investment decisions across the cards and lending lifecycles — from eligibility and activation to spend, retention, incentives, and credit performance. You’ll help build a data-informed culture across Mercury so teams can move quickly, measure what matters, and invest intelligently.
Here are some things you’ll do on the job:
Bring impeccable communication and complete ownership — independently identifying opportunities, developing strong points of view, and influencing executives, Cards & Credit leaders, and cross-functional partners through clear, concise, and persuasive storytelling.
Develop a nuanced understanding of cardholder behavior and economics, helping teams reason about tradeoffs between growth, engagement, risk, and unit economics.
Define, own, and analyze metrics that inform both tactical decisions and long-term strategy across the cards and credit lifecycle (e.g., eligibility, activation, spend, utilization, rewards, retention, loss signals).
Design and evaluate experiments using rigorous statistical approaches, including A/B testing, cohort analysis, causal inference techniques, and trend analysis.
Build and improve data pipelines and tools to streamline data collection, processing, and analysis workflows, ensuring the integrity, reliability, and security of data assets.
You should:
Bring 7+ years of experience working with large datasets to drive product or business impact in data science or analytics roles.
Be fluent in SQL and comfortable with python.
Demonstrate strong judgment in defining and analyzing product metrics, running experiments, and translating ambiguous questions into structured analyses.
Operate with exceptional proactivity and independence — identifying opportunities, forming strong points of view, and making your case to stakeholders.
Be experienced with modern analytics and data modeling stacks (e.g., dbt, dimensional models), with a solid understanding of how data is produced and consumed.
Apply AI tools to accelerate analytical and business workflows, improving scalability, decision quality, and reducing manual or repetitive work across teams.
Nice to have:
Experience working on cards or credit products, such as corporate cards, charge cards, consumer cards, or revolving credit products.
Familiarity with card economics and lifecycle concepts, including spend behavior, interchange, rewards and incentives, utilization, credit limits, and retention.
Experience leveraging underwriting inputs, lifecycle risk signals, or third-party credit data to inform or optimize credit strategy or product decisions.
Experience building or supporting credit models for cards or lending products, including probability of default modeling, credit limit setting, or portfolio monitoring.
The total rewards package at Mercury includes base salary, equity (stock options), 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 (any location): $200,700 - $250,900 USD
Canadian employees (any location): CAD 189,700 - 237,100
Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.
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.
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.]
#LI-RA1