Koalafi Is Hiring
At Koalafi, we believe in a world where no one has to put an important purchase on hold. That’s why we’re making it easier for more people to pay for big purchases over time.
Retailers across the country rely on us to offer flexible lease-to-own financing to their non-prime consumers, while increasing sales and strengthening customer loyalty. Their 2M+ customers love us because we provide a flexible way for them to make payments and give them an opportunity to improve their credit. Our 200+ Koalafi teammates enjoy inspiring and challenging work that accelerates their careers.
Interested in learning more about how we’re transforming the financing experience and joining our team?
What You’ll Do Are you a senior-level data scientist with a passion for building and deploying high-impact fraud or credit risk models? Koalafi is seeking an experienced Data Scientist to lead the development, deployment, and monitoring of machine learning models that sit at the core of our portfolio’s profitability. This role requires someone who thrives in an end-to-end environment—designing predictive models, operationalizing them in production, and ensuring they continue to perform in a dynamic market.
You will be a key contributor to Koalafi’s decisioning ecosystem, owning models that directly influence credit outcomes, fraud mitigation, and the financial performance of the company. Beyond technical expertise, you will bring strong business intuition, enabling you to translate modeling insights into strategic decisions. This position reports to the Manager of Data Science and regularly partners with senior leaders across Risk, Fraud, Analytics, and Technology.
Responsibilities
Build, deploy, and maintain production‑grade credit and fraud models that are foundational to our real‑time decisioning platform and essential to portfolio profitability
Own the full MLOps lifecycle—from feature engineering, model training, and experiment management to production deployment, performance monitoring, drift detection, and continuous optimization
Architect and scale end‑to‑end ML pipelines, ensuring reliability, reproducibility, and seamless integration with core decisioning services
Design robust model monitoring frameworks that enable tracing, profiling, explainability, and rapid root‑cause analysis for production incidents or model degradation
Partner with data science, risk, and engineering leaders to shape modeling strategy, improve credit policy, and strengthen fraud defenses in response to customer behavior and macroeconomic trends
Drive continuous improvement of existing models, incorporating new data sources, advanced techniques, and rigorous validation processes
Communicate complex model logic and insights to non‑technical stakeholders, clearly linking modeling decisions to business outcomes and strategic priorities
About You
5+ years of hands‑on experience building and deploying machine learning models, with a strong grasp of the end‑to‑end modeling lifecycle from feature engineering to validation and productionization
5+ years of professional experience writing performant, maintainable Python code in a collaborative production environment, leveraging core data science libraries like pandas, numpy, xgboost, and scikit‑learn
2+ years of experience working on Credit or Fraud risk models
Proficient in SQL for querying, transforming, and analyzing large datasets, and comfortable working across relational databases and cloud‑based data platforms
Strong understanding of data structures, algorithms, and software engineering principles, and apply them to build robust and scalable data solutions
Bachelor’s degree in a quantitative or STEM field (e.g., Statistics, Mathematics, Computer Science, Engineering) and demonstrate strong analytical and problem‑solving skills in your work
Location Requirement:
This position requires regular in‑person attendance at one of our two office locations (Richmond, VA or Arlington, VA). Candidates must already be located within a commutable distance to either location, as relocation assistance is not available at this time.
Preferred Qualifications
Advanced technical and analytical background, ideally with a Master’s or PhD in a quantitative or STEM field, and a strong understanding of probability, statistics, and predictive modeling algorithms (e.g., Boosting, Random Forests, Decision Trees, Bayesian models)
Exposure to data and compute platforms such as Snowflake and Databricks
Background in financial services or experience working in fast‑moving, high‑growth environments such as startups
Experience with modern ML infrastructure and tooling, including MLOps frameworks (e.g., MLflow, BentoML), CI/CD automation, and model observability, monitoring, and lifecycle management
Familiarity with large language models (LLMs) and their deployment in production environments
Why choose Koalafi:
A career at Koalafi means opportunities to tackle exciting challenges every single day. We take pride in a culture of innovation, trust, and ownership. You'll get outside your comfort zone, build meaningful relationships, and most of all, take charge of projects that ultimately help people get the things they need most.
At Koalafi, you will have a direct impact on our products and help shape the company’s success. We offer competitive compensation & benefits packages to keep you at your best:
Comprehensive medical, dental, and vision coverage
20 PTO days + 11 paid holidays
401(k) retirement with company matching
Commuter assistance
Parental leave (maternal + paternal)
Inclusion and Associate Engagement Programs
Who we are & what we value:
We focus on what’s most important
We set clear expectations and deliver
We embrace challenges to reach our full potential
We ask, “How can this be better?”
We move fast together
Voluntary Self‑Identification For government reporting purposes, we ask candidates to respond to the below self‑identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.
As set forth in Koalafi’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows:
A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service‑connected disability.
A "recently separated veteran" means any veteran during the three‑year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.
An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.
An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.
We are a federal contractor or subcontractor. The law requires us to provide equal employment opportunity to qualified people with disabilities. We have a goal of having at least 7% of our workers as people with disabilities. The law says we must measure our progress towards this goal. To do this, we must ask applicants and employees if they have a disability or have ever had one. People can become disabled, so we need to ask this question at least every five years.
Completing this form is voluntary, and we hope that you will choose to do so. Your answer is confidential. No one who makes hiring decisions will see it. Your decision to complete the form and your answer will not harm you in any way. If you want to learn more about the law or this form, visit the U.S. Department of Labor’s Office of Federal Contract Compliance Programs (OFCCP) website at https://www.dol.gov/ofccp.
How do you know if you have a disability?
A disability is a condition that substantially limits one or more of your “major life activities.” If you have or have ever had such a condition, you are a person with a disability.
Disabilities include, but are not limited to:
Alcohol or other substance use disorder (not currently using drugs illegally)
Autoimmune disorder, for example, lupus, fibromyalgia, rheumatoid arthritis, HIV/AIDS
Blind or low vision
Cancer (past or present)
Cardiovascular or heart disease
Celiac disease
Cerebral palsy
Deaf or serious difficulty hearing
Diabetes
Disfigurement, for example, disfigurement caused by burns, wounds, accidents, or congenital disorders
Epilepsy or other seizure disorder
Gastrointestinal disorders, for example, Crohn's Disease, irritable bowel syndrome
Intellectual or developmental disability
Mental health conditions, for example, depression, bipolar disorder, anxiety disorder, schizophrenia, PTSD
Missing limbs or partially missing limbs
Mobility impairment, benefiting from the use of a wheelchair, scooter, walker, leg brace(s) and/or other supports
Nervous system condition, for example, migraine headaches, Parkinson’s disease, multiple sclerosis (MS)
Neurodivergence, for example, attention‑deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities
Partial or complete paralysis (any cause)
Pulmonary or respiratory conditions, for example, tuberculosis, asthma, emphysema
Short stature (dwarfism)
Traumatic brain injury
PUBLIC BURDEN STATEMENT: According to the Paperwork Reduction Act of 1995 no persons are required to respond to a collection of information unless such collection displays a valid OMB control number. This survey should take about 5 minutes to complete.
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Retailers across the country rely on us to offer flexible lease-to-own financing to their non-prime consumers, while increasing sales and strengthening customer loyalty. Their 2M+ customers love us because we provide a flexible way for them to make payments and give them an opportunity to improve their credit. Our 200+ Koalafi teammates enjoy inspiring and challenging work that accelerates their careers.
Interested in learning more about how we’re transforming the financing experience and joining our team?
What You’ll Do Are you a senior-level data scientist with a passion for building and deploying high-impact fraud or credit risk models? Koalafi is seeking an experienced Data Scientist to lead the development, deployment, and monitoring of machine learning models that sit at the core of our portfolio’s profitability. This role requires someone who thrives in an end-to-end environment—designing predictive models, operationalizing them in production, and ensuring they continue to perform in a dynamic market.
You will be a key contributor to Koalafi’s decisioning ecosystem, owning models that directly influence credit outcomes, fraud mitigation, and the financial performance of the company. Beyond technical expertise, you will bring strong business intuition, enabling you to translate modeling insights into strategic decisions. This position reports to the Manager of Data Science and regularly partners with senior leaders across Risk, Fraud, Analytics, and Technology.
Responsibilities
Build, deploy, and maintain production‑grade credit and fraud models that are foundational to our real‑time decisioning platform and essential to portfolio profitability
Own the full MLOps lifecycle—from feature engineering, model training, and experiment management to production deployment, performance monitoring, drift detection, and continuous optimization
Architect and scale end‑to‑end ML pipelines, ensuring reliability, reproducibility, and seamless integration with core decisioning services
Design robust model monitoring frameworks that enable tracing, profiling, explainability, and rapid root‑cause analysis for production incidents or model degradation
Partner with data science, risk, and engineering leaders to shape modeling strategy, improve credit policy, and strengthen fraud defenses in response to customer behavior and macroeconomic trends
Drive continuous improvement of existing models, incorporating new data sources, advanced techniques, and rigorous validation processes
Communicate complex model logic and insights to non‑technical stakeholders, clearly linking modeling decisions to business outcomes and strategic priorities
About You
5+ years of hands‑on experience building and deploying machine learning models, with a strong grasp of the end‑to‑end modeling lifecycle from feature engineering to validation and productionization
5+ years of professional experience writing performant, maintainable Python code in a collaborative production environment, leveraging core data science libraries like pandas, numpy, xgboost, and scikit‑learn
2+ years of experience working on Credit or Fraud risk models
Proficient in SQL for querying, transforming, and analyzing large datasets, and comfortable working across relational databases and cloud‑based data platforms
Strong understanding of data structures, algorithms, and software engineering principles, and apply them to build robust and scalable data solutions
Bachelor’s degree in a quantitative or STEM field (e.g., Statistics, Mathematics, Computer Science, Engineering) and demonstrate strong analytical and problem‑solving skills in your work
Location Requirement:
This position requires regular in‑person attendance at one of our two office locations (Richmond, VA or Arlington, VA). Candidates must already be located within a commutable distance to either location, as relocation assistance is not available at this time.
Preferred Qualifications
Advanced technical and analytical background, ideally with a Master’s or PhD in a quantitative or STEM field, and a strong understanding of probability, statistics, and predictive modeling algorithms (e.g., Boosting, Random Forests, Decision Trees, Bayesian models)
Exposure to data and compute platforms such as Snowflake and Databricks
Background in financial services or experience working in fast‑moving, high‑growth environments such as startups
Experience with modern ML infrastructure and tooling, including MLOps frameworks (e.g., MLflow, BentoML), CI/CD automation, and model observability, monitoring, and lifecycle management
Familiarity with large language models (LLMs) and their deployment in production environments
Why choose Koalafi:
A career at Koalafi means opportunities to tackle exciting challenges every single day. We take pride in a culture of innovation, trust, and ownership. You'll get outside your comfort zone, build meaningful relationships, and most of all, take charge of projects that ultimately help people get the things they need most.
At Koalafi, you will have a direct impact on our products and help shape the company’s success. We offer competitive compensation & benefits packages to keep you at your best:
Comprehensive medical, dental, and vision coverage
20 PTO days + 11 paid holidays
401(k) retirement with company matching
Commuter assistance
Parental leave (maternal + paternal)
Inclusion and Associate Engagement Programs
Who we are & what we value:
We focus on what’s most important
We set clear expectations and deliver
We embrace challenges to reach our full potential
We ask, “How can this be better?”
We move fast together
Voluntary Self‑Identification For government reporting purposes, we ask candidates to respond to the below self‑identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.
As set forth in Koalafi’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows:
A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service‑connected disability.
A "recently separated veteran" means any veteran during the three‑year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.
An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.
An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.
We are a federal contractor or subcontractor. The law requires us to provide equal employment opportunity to qualified people with disabilities. We have a goal of having at least 7% of our workers as people with disabilities. The law says we must measure our progress towards this goal. To do this, we must ask applicants and employees if they have a disability or have ever had one. People can become disabled, so we need to ask this question at least every five years.
Completing this form is voluntary, and we hope that you will choose to do so. Your answer is confidential. No one who makes hiring decisions will see it. Your decision to complete the form and your answer will not harm you in any way. If you want to learn more about the law or this form, visit the U.S. Department of Labor’s Office of Federal Contract Compliance Programs (OFCCP) website at https://www.dol.gov/ofccp.
How do you know if you have a disability?
A disability is a condition that substantially limits one or more of your “major life activities.” If you have or have ever had such a condition, you are a person with a disability.
Disabilities include, but are not limited to:
Alcohol or other substance use disorder (not currently using drugs illegally)
Autoimmune disorder, for example, lupus, fibromyalgia, rheumatoid arthritis, HIV/AIDS
Blind or low vision
Cancer (past or present)
Cardiovascular or heart disease
Celiac disease
Cerebral palsy
Deaf or serious difficulty hearing
Diabetes
Disfigurement, for example, disfigurement caused by burns, wounds, accidents, or congenital disorders
Epilepsy or other seizure disorder
Gastrointestinal disorders, for example, Crohn's Disease, irritable bowel syndrome
Intellectual or developmental disability
Mental health conditions, for example, depression, bipolar disorder, anxiety disorder, schizophrenia, PTSD
Missing limbs or partially missing limbs
Mobility impairment, benefiting from the use of a wheelchair, scooter, walker, leg brace(s) and/or other supports
Nervous system condition, for example, migraine headaches, Parkinson’s disease, multiple sclerosis (MS)
Neurodivergence, for example, attention‑deficit/hyperactivity disorder (ADHD), autism spectrum disorder, dyslexia, dyspraxia, other learning disabilities
Partial or complete paralysis (any cause)
Pulmonary or respiratory conditions, for example, tuberculosis, asthma, emphysema
Short stature (dwarfism)
Traumatic brain injury
PUBLIC BURDEN STATEMENT: According to the Paperwork Reduction Act of 1995 no persons are required to respond to a collection of information unless such collection displays a valid OMB control number. This survey should take about 5 minutes to complete.
#J-18808-Ljbffr