What You’ll Do 

Koalafi is expanding beyond lease-to-own by launching a non-prime installment loan product that will diversify our portfolio and accelerate growth in select states and verticals.  The Manager of Business Analysis will report directly to the Chief Risk Officer and play a central role in designing and operationalizing the company’s risk management framework for this new product.  The role will lead development of core risk policies (credit, fraud, KYC/AML, collections, etc.), build a robust monitoring and reporting suite, and execute ad hoc analyses that support product development, pilot rollout, and scaling. This person will be a key cross-functional partner to Product, Engineering, Compliance/Legal, Operations, and Finance. 

Risk Policy Development & Governance 

• Lead drafting and iteration of risk management policies and standards supporting the non-prime installment product, including: 
  • Credit policy (eligibility, underwriting strategy, line assignment, and pricing inputs) 
  • Fraud policy (identity theft, synthetic fraud, first-party fraud, and merchant abuse)
  • KYC / identity verification standards (CIP/KYC requirements, documentary verification requirements, third-party data use, and step-up verification)
  • Servicing and collections risk policy (hardship, restructures, settlements, and outbound communications) 

• Translate policy intent into operational procedures and control requirements 

• Establish a lightweight governance cadence for policy review/changes and maintain a living policy repository with change logs 

Monitoring Suite & Risk Reporting 

• Design and implement a monitoring framework for the new product that includes: 
  • Risk appetite metrics and early-warning indicators (origination mix, approval rates, early DQ, roll rates, fraud rate, payment failure rates, complaint rate, etc.) 
  • Cohort/vintage tracking and performance segmentation (state, vertical, channel, merchant, score band, income/DTI bands, etc.)
  • Operational controls monitoring (KYC pass rates, step-up rates, manual review queues, etc.) 

• Build a recurring executive reporting pack for the leadership team and create self-serve dashboards for day-to-day decision making. 

• Partner with Analytics and Data Engineering to ensure data definitions are consistent, auditable, and scalable (metric dictionary, QA checks, reconciliation vs. source systems). 

Product Launch Support & Ad Hoc Analysis 

• Support product design decisions by quantifying trade-offs among risk, approval rate, unit economics, and customer experience (e.g., pricing sensitivity, repayment term structures, down payment requirements, etc.). 

• Conduct targeted analyses to inform rollout strategy by state and vertical, including regulatory-driven constraints and operational readiness. 

• Partner with Product and Engineering on test design and evaluation (A/B tests, pilots, phased rollouts), including measurement plans and success criteria. 

Cross-Functional Influence & Execution 

• Serve as a primary risk analytics partner to Product/Engineering during build, ensuring risk requirements are embedded in workflows (application, underwriting, funding, servicing, and collections). 

• Collaborate closely with Compliance/Legal to translate regulatory requirements into operational policy and monitoring. 

• Coordinate with Operations to ensure procedures, training, and escalation pathways align with policy intent. 

• Drive clarity in decision-making: define owners, timelines, and expected deliverables; keep stakeholders aligned through launch milestones. 

What Success Looks Like (First 6–12 Months) 

• Core risk policies for the installment product are drafted, approved, and operationalized with clear change-control and exception processes. 

• A “first-class” monitoring suite is live with daily/weekly dashboards and a monthly executive risk review cadence. 

• Leadership has clear visibility into product performance by state/vertical, with early-warning signals and action plans. 

• Policy and monitoring enable a controlled rollout that meets regulatory needs while achieving target approval and loss-rate ranges. 

About You (Qualifications) 

• Bachelor’s degree required, in a quantitative field such as Statistics, Mathematics, Economics, Business, or Engineering preferred 

• 5+ years of experience in an analyst, data science, or consulting role 

• 3+ years of experience in credit risk analytics 

• Experience in consumer financing industry, such as credit cards, personal loans, auto loans, BNPL, or similar field 

• Proficiency in Excel, SQL, and Python for data analysis 

• Exceptional attention to detail and problem-solving skills 

• Ability to create a strategic agenda and execute against it 

• Desire to work in a fast-paced, dynamic entrepreneurial environment 

• Strong written and verbal communication skills 

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.

What You’ll Do 

The Sr. Director of Credit Risk Analytics is a senior leadership role responsible for the full Credit Policy function — from strategy design through execution and measurement. You will own the credit program's analytical infrastructure, set the team's agenda, and be the primary accountable owner for portfolio profitability. This is a high-visibility role that requires equal parts strategic vision and quantitative rigor, with a strong bias toward structured experimentation and evidence-based decision-making. 

You will report directly to the Chief Risk Officer and serve as a key cross-functional partner to the Data Science, Finance, Product/Tech, and Sales teams. 

Credit Policy Strategy & Program Ownership 

• Define and own the Credit Policy roadmap, setting the team's agenda in alignment with company growth, risk appetite, and profitability objectives
• Determine which underwriting strategies, credit policy levers, and product term configurations to pursue — and in what sequence
• Partner with the Data Science team to translate policy intent into model inputs, scorecard strategies, and decisioning logic
• Ensure that credit policy decisions account for second-order effects, including merchant engagement and performance impacts associated with changes 

Experimentation & Strategy Measurement 

• Design, execute, and monitor controlled experiments (A/B tests, champion/challenger frameworks) for all material credit policy and product term changes prior to full rollout
• Establish rigorous experimental design standards that ensure clean attribution — isolating the impact of individual policy changes from macro, seasonal, and cohort effects
• Define the measurement framework for each test, identifying the appropriate primary and guardrail metrics
• Synthesize test results into clear, defensible recommendations and present findings to senior leadership and cross-functional partners 

Portfolio Performance Monitoring & Analytics 

• Own ongoing monitoring of portfolio health across a comprehensive suite of KPIs, including delinquency rates, roll rates, early buyout rates, loss curves, and terminal outcomes by cohort, vintage, vertical, and channel
• Build and maintain analytical frameworks that allow the team to quickly surface emerging portfolio trends and distinguish signal from noise
• Identify risk concentrations, underperforming segments, and policy gaps, and drive timely remediation through credit policy adjustments 

Portfolio Forecasting 

• Lead portfolio forecasting using a combination of horizontal and vertical performance metrics to produce reliable point-in-time portfolio performance projections
• Partner with FP&A and Capital Markets to ensure credit forecasts are integrated into financial planning, capital allocation, and investor reporting processes
• Develop scenario analysis and stress-testing capabilities to assess the portfolio's sensitivity to macroeconomic changes, product mix shifts, and channel growth assumptions 

Valuations Framework & Unit Economics 

• Design and own a valuations framework and model that enables analysts on the team to rapidly and reliably model the unit economics impact of changes to credit policy, product terms, and origination mix
• Ensure the model is flexible enough to support "what-if" scenario gaming across key levers (e.g., APR equivalents, payment cadence, term length, approval tier thresholds) while maintaining analytical integrity
• Work with Finance and Capital Markets to align valuation assumptions with capital markets pricing, funding cost structures, and investor reporting standards 

Team Leadership & Development 

• Lead, mentor, and develop a team of four: a Senior Analyst, Manager, Senior Manager, and Director — establishing clear goals, growth paths, and accountability structures
• Foster a culture of intellectual rigor, curiosity, and ownership within the team
• Build scalable analytical processes and documentation standards that reduce key-person dependency and support team growth as the business scales
• Represent the Credit Policy function in cross-functional forums and serve as a thought partner to peer leaders across Risk, Data Science, Product, and Finance 

About You (Qualifications) 

• Bachelor’s degree required, in a quantitative field such as Statistics, Mathematics, Economics, Business, or Engineering preferred
• 7+ years of experience in an analyst, data science, or consulting role
• 5+ years of experience in credit risk analysis, credit policy, or a closely related function within consumer or small business lending, leasing, or installment finance
• Prior experience with Lease-to-Own, BNPL, installment lending, other non-traditional consumer credit products preferred 
• Deep proficiency in credit performance analytics: delinquency curves, roll rate analysis, loss forecasting, vintage analysis, and cohort-based performance attribution
• Expert-level command of experimental design, including A/B testing, champion/challenger frameworks, and statistical significance testing; a demonstrated ability to isolate causal effects and defend attribution in complex, multi-variable environments
• Strong financial modeling skills including the ability to translate credit performance assumptions into unit economics, portfolio valuations, and P&L impact
• Proficiency in Excel, SQL, and Python; comfort working with large datasets and interfacing with data science and data engineering teams
• Proven ability to lead and develop analytical teams, including managing managers
• Exceptional communication skills — able to translate complex quantitative findings into crisp, actionable narratives for executive and cross-functional audiences
• High degree of intellectual honesty; comfortable challenging assumptions, acknowledging uncertainty, and changing course when data warrants it
• Strong instincts for prioritization in a fast-moving, resource-constrained environment 
• 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.

About Koalafi

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.

Over 17,000 retailers rely on us to match their customers to a payment plan clearly and quickly, all while reflecting well on their brand. 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.

What You’ll Do

Fraud is one of the largest challenges plaguing financial institutions today, with an estimated $27 billion in annual losses from identity theft alone1. In addition to identity theft, there is a growing trend of synthetic IDs, manipulated IDs, and scam incidents. 

Koalafi is continuing to scale its payments and financing platform across direct-to-consumer and merchant channels. As fraud attack strategies evolve alongside this growth, the company is investing in stronger and more adaptive fraud defenses. The Manager of Business Analytics – Fraud will report directly to the Director of Fraud Strategy & Analytics and play a central role in developing and optimizing Koalafi’s fraud risk strategy. 

This role will lead analytical efforts to develop and iterate fraud policies, evaluate new fraud defense capabilities and data sources, and strengthen fraud monitoring and reporting frameworks. The position will focus on improving Koalafi’s resilience against evolving fraud trends while enabling responsible growth across new products, channels, and partners. This individual will serve as a key analytical partner to Product, Engineering, Risk Operations, and other cross-functional teams to ensure fraud controls are effectively embedded in customer and merchant workflows. 

Fraud Policy Development 

Lead the analysis and continuous improvement of Koalafi’s fraud defense framework, including policies, decision rules, thresholds, and model targeting. 

Responsibilities include: 

• Analyze fraud trends and attack patterns to continuously strengthen automated and manual fraud defenses. 

• Develop and iterate fraud defense strategy (rules, policies, thresholds, decision logic) to maintain strong protection against both ambient fraud activity and coordinated fraud attacks. 

• Design and implement defenses tailored to emerging channels, including direct-to-consumer, to support enterprise-wide scaling initiatives. 

• Evaluate and integrate new fraud detection capabilities, tools, and third-party data sources that improve risk detection and operational efficiency. 

• Enhance and optimize merchant-level fraud risk monitoring and reporting, identifying patterns that may indicate merchant abuse or elevated risk exposure. 

Monitoring Suite & Risk Reporting 

Improve and scale the fraud monitoring framework to ensure early detection of emerging threats and clear visibility into fraud performance. 

Responsibilities include: 

• Develop and enhance fraud monitoring dashboards and reporting that track fraud performance metrics and trends across customer segments, merchant verticals, and channels. 

• Build analytical tools and monitoring processes designed to detect segment-level anomalies and emerging fraud patterns. 

• Implement automated alerting and anomaly detection to enable timely response to new fraud threats. 

• Partner with Analytics and Data teams to ensure fraud metrics and reporting are accurate, scalable, and aligned across systems. 

Product Launch Support & Ad Hoc Analysis 

Support new product launches and business initiatives by providing analytical insights into fraud risk and mitigation strategies. 

Responsibilities include: 

• Support product design and rollout decisions by quantifying trade-offs among fraud risk, approval rate, unit economics, and customer experience. 

• Conduct targeted analyses to evaluate fraud exposure across new merchant partners, verticals, and products. 

• Monitor fraud performance during product launches, pilots, and scaling phases, identifying early indicators of emerging risk. 

• Provide ad hoc analytical support for fraud strategy initiatives and evolving risk mitigation efforts. 

Cross-Functional Influence & Execution 

Serve as a key analytical partner across teams to ensure fraud defenses are embedded effectively within Koalafi’s products and operational processes. 

Responsibilities include: 

• Partner closely with Product and Engineering teams during product development to ensure fraud risk controls are built into key workflows. 

• Collaborate with Risk Operations to ensure manual review processes align with fraud policy intent and evolving fraud patterns. 

• Provide analytical insights that support clear decision-making across stakeholders and initiatives. 

• Help drive alignment across teams by defining project milestones, delivering analytical insights, and maintaining effective communication with key stakeholders. 

 About You (Qualifications) 

• Bachelor’s degree required, in a quantitative field such as Statistics, Mathematics, Economics, Business, or Engineering preferred 

• 5+ years of experience in an analyst, data science, or consulting role 

• 3+ years of experience in fraud risk analytics 

• Experience in consumer financing industry, such as credit cards, personal loans, auto loans, BNPL, or similar fields 

• Proficiency in Excel, SQL, and Python for data analysis 

• Exceptional attention to detail and strong problem-solving skills 

• Ability to develop strategic project plans and execute against them 

• Desire to work in a fast-paced, dynamic entrepreneurial environment 

• Strong written and verbal communication skills 
  
  
• 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.

What You’ll Do 

Koalafi is seeking a Manager of Business Analytics to build the frameworks, measurement systems, and analytical foundations that ensure our product releases drive their intended impact—without unintended downstream consequences. This high-visibility role will own the definition, tracking, and automated monitoring of core KPIs across product journeys and operational workflows. This is an individual contributor role at the Manager level.

In this role, you’ll work primarily with Product, Engineering, and Analytics partners to design robust measurement strategies for existing and new initiatives, implement automated alerting for anomalies, and ensure that each release is evaluated against clearly defined success criteria. You will also lead key efforts to optimize the return customer experience, identify opportunities to improve mobile app engagement, and drive long-term product performance improvements.

This is a rare opportunity to establish the backbone of product analytics for a high-growth fintech company—while creating clarity, accountability, and data-driven decision-making across the organization.

KPI Definition, Tracking & Alerting

• Define and maintain the authoritative set of product KPIs across application flows, customer lifecycle stages, operational behaviors, and internal decisioning systems.
• Build product measurement frameworks and documentation that clearly articulate intended outcomes, guardrails, and dependence on upstream systems.
• Partner with product managers and engineering leads to integrate KPI measurement into release planning and acceptance criteria.
• Develop automated alerts to detect anomalies, degradation, or unexpected movement in key product metrics.
• Implement monitoring dashboards that give product and business stakeholders real-time visibility into performance.
• Establish processes to investigate, triage, and communicate the root cause of KPI changes.

Product Impact Evaluation

• Analyze the impact of new product releases, policy changes, and UX improvements using well-defined baselines and control groups.
• Ensure downstream effects across approval rates, customer behavior, repayment performance, or operational workflows are measured and understood.
• Provide clear insights and recommendations that influence product prioritization and roadmap decisions.

Customer and App Experience Optimization

• Review and optimize experiences for returning customers, including friction points, drop-off behavior, and policy interactions.
• Analyze mobile app engagement patterns to identify opportunities for UX enhancements, feature prioritization, and content improvements.
• Partner with product teams to design and evaluate experiments aimed at increasing engagement, conversion, and retention.

Cross-Functional Expansion

• Create a scalable measurement and alerting framework that can be extended beyond Product—next with Legal and Compliance.
• Work with these teams to define key compliance KPIs, build monitoring processes, and ensure alignment with regulatory expectations.
• Partner with cross-functional leads to drive clarity and shared ownership of analytical definitions.

About You (Qualifications) 

• Bachelor’s degree in a quantitative, analytical, or product-related field (e.g., Engineering, Statistics, Economics, Computer Science, Product Management).
• 4–6 years of experience in product analytics, business analysis, product management, or a related field.
• Strong experience defining and measuring KPIs within digital products, operational workflows, or financial systems, ideally in consumer lending or lease-to-own finance.
• Proficiency with SQL and experience analyzing large datasets.
• Experience building dashboards and automated monitoring systems (Tableau, Looker, or similar).
• Familiarity with experiment design, measurement strategy, and release evaluation frameworks.
• Comfortable working in an ambiguous, fast-paced environment and excited to build foundational systems from scratch.
• Excellent communication skills, with the ability to translate complex analytical findings into clear recommendations for product and business leaders.
• You have a growth mindset and are comfortable giving and receiving feedback to continuously learn and grow.
• Detail-oriented, proactive, and motivated by curiosity, structure-building, and continuous improvement.
• 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.

The Opportunity

As Director of Risk Operations, you will own end-to-end operational fraud prevention and risk review across both our merchant and customer portfolios. You will lead a team of six Fraud Investigators, setting the direction, building the processes, and developing the capabilities that allow Koalafi to scale its fraud prevention function as the business grows.

This is a hands-on leadership role at a company of ~220 people, meaning you will be both a strategic owner and an active contributor. You'll be expected to roll up your sleeves — diving into complex investigations, designing workflows, writing documentation, and coaching your team — while simultaneously thinking about how the function needs to evolve over the next 12-24 months.

The right person for this role sees process excellence and technology adoption not as administrative overhead, but as the core levers for building a fraud operation that punches above its weight. You are genuinely excited about AI and actively experimenting with how it can be applied to fraud workflows — not as a future aspiration, but as something you are doing right now.

What You’ll Own

Merchant Underwriting

• Oversee the risk assessment and approval process for all new merchant partners during onboarding
• Ensure the team is consistently applying sound underwriting judgment to evaluate merchant legitimacy, business quality, and fraud risk
• Develop and maintain underwriting standards, decision frameworks, and documentation that create consistency and auditability across the team
• Identify patterns in merchant approvals and denials that can inform policy improvements over time

Merchant Fraud Reviews

• Lead the ongoing monitoring and investigation of approved merchants exhibiting suspicious activity or abnormally poor account performance
• Build and refine the triggers, workflows, and escalation paths that govern when and how merchants are reviewed
• Own merchant disposition decisions — clear, escalate, restrict, or terminate — and ensure those decisions are well-documented and defensible
• Collaborate with Sales and Account Management on difficult merchant situations requiring cross-functional coordination

Proactive Customer-Level Fraud Reviews

• Oversee the review of customer applications flagged at medium risk levels — cases that scored above automatic approval thresholds but below automatic decline thresholds
• Ensure the team is applying consistent investigative standards using available tools including application data, internal systems, and third-party fraud prevention platforms
• Continuously evaluate queue volumes, disposition rates, and outcomes to identify opportunities to sharpen automated decisioning and reduce manual review burden

Reactive Customer-Level Fraud Reviews

• Own the intake and resolution process for inbound fraud claims, disputes, and complaints submitted through escalation channels
• Ensure timely, accurate, and compliant handling of all reactive cases in accordance with regulatory requirements and internal SLAs
• Identify systemic patterns in reactive volume that signal upstream process gaps or emerging fraud typologies

Post-Funding Account-Level Reviews

• Manage reviews triggered by suspicious activity at the account or customer level after funding has occurred
• Develop and refine the signals and rules that trigger post-funding review
• Collaborate with Fraud Analytics to ensure post-funding findings feed back into model development and strategy

How You'll Lead

• Team leadership: Directly manage a team of six Fraud Investigators, providing day-to-day coaching, structured feedback, and clear performance expectations
• Process development: Design, document, and continuously improve the workflows, decision frameworks, and standard operating procedures that govern every review type under your scope
• Training: Build and maintain a training program that onboards new investigators effectively and keeps the existing team sharp as fraud typologies and tools evolve
• Quality assurance: Establish a QA process to monitor decision consistency, catch errors, and create a feedback loop that raises the team's overall standard
• Cross-functional collaboration: Work closely with Fraud Analytics, Compliance, Sales, Operations, and Product to ensure Risk Operations is well-integrated into the broader business
• Escalation management: Serve as the final escalation point for complex or high-stakes cases that require senior judgment

AI and Technology

This role requires more than comfort with technology — it requires genuine curiosity and initiative in applying AI to fraud operations. You will:

• Actively experiment with AI tools (including large language models, automation platforms, and agentic workflows) to identify opportunities to improve investigator efficiency and decision quality
• Lead the evaluation and adoption of new fraud prevention technologies and third-party tools
• Work with Fraud Analytics and Engineering to scope and prioritize tooling investments that support the team
• Bring a point of view on where AI can realistically augment or automate portions of the fraud review workflow — and be willing to build and test those ideas, not just propose them

About You

 Experience

• 6+ years of experience in fraud operations, fraud investigations, or risk management within a financial services or fintech environment
• 2+ years of people management experience, with a track record of developing individual contributors
• Direct experience with merchant fraud, point-of-sale financing, or B2B2C financial products strongly preferred
• Familiarity with consumer regulatory requirements relevant to fraud and disputes (CFPB, FCRA, Reg E, UDAAP)

Skills and Orientation

• Strong process improvement orientation — you find poorly documented, inconsistent workflows genuinely uncomfortable and are motivated to fix them
• Excellent written communication skills; you write clear, structured documentation that others can easily follow
• Sharp pattern recognition and investigative instincts — you can identify what's anomalous and pursue it methodically
• Comfortable making and defending judgment calls in ambiguous situations with incomplete information
• Data literate — you can work with Excel and basic reporting tools to monitor team performance and identify trends; SQL familiarity is a plus
• Collaborative and low-ego; this is a small company and you'll need to work effectively across functions without a large support structure

Mindset

• Genuinely excited about AI and actively experimenting with how it applies to your domain — not waiting to be told, but exploring on your own
• Orientation toward building scalable systems rather than heroic individual effort
• Strong sense of ethics and confidentiality — you understand the sensitivity of the information this role handles
• Comfortable having difficult conversations with merchants, internal stakeholders, and leadership
• Motivated by catching fraud and building something that makes that easier over time