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Lead Risk Analyst
$100 - $125k
1
Denver, CO
About the Role
The Lead Risk Analyst will spearhead our risk management and fraud prevention efforts, ensuring that our fintech platform maintains the highest standards of security and compliance as we scale. In this role, you will own the monitoring and analysis of transaction activities and customer behaviors to detect fraud, mitigate risks, and protect both the company and our clients from losses or regulatory issues. As an early hire focused on risk, you’ll establish the policies, tools, and procedures we use to keep our payment system safe. This includes everything from analyzing patterns in transactional data for suspicious activity, to fine-tuning our risk scoring algorithms, to ensuring we meet compliance obligations like KYC (Know Your Customer) and AML (Anti-Money Laundering) regulations.
On a daily basis, you will review alerts generated by our transaction monitoring systems (for example, flags for unusual transfer amounts or frequency, identity mismatches, etc.). You’ll investigate these alerts in depth: using internal dashboards and databases to gather information about the users or transactions in question, and deciding on the appropriate action (such as holding a payout, requiring additional verification, or clearing a false alarm). You will work closely with our Technical Lead for Data Science to continuously improve the risk models and rules – providing feedback on what patterns you’re seeing, and helping to test model updates. Additionally, you’ll handle the compliance side of risk analysis: overseeing KYC and watchlist screening results for new customers, and making sure we follow proper procedures if any user hits a sanctions list or raises red flags.
Because this is a leadership role in a startup context, you will also be setting up the risk management framework that future analysts will follow. This means documenting policies (risk scoring criteria, investigation steps), selecting and implementing fraud detection tools as needed, and training other team members on risk-aware practices. You will liaise with external partners or regulators if required, perhaps in the event of fraud incidents or audits. Over time, as our volume grows, you may build and manage a small team of risk analysts. The role is full-time in Denver, CO (with remote flexibility) and comes with a combination of salary and equity. It’s an exciting opportunity to shape the risk culture and systems from the ground up at a rising fintech startup.
Key Responsibilities
Transaction Monitoring & Analysis – Continuously monitor ongoing transactions and account activities through our risk dashboards and automated alert systems. Analyze transactions that trigger fraud alerts or fall outside normal patterns (e.g., unusually large ACH transfers, multiple rapid attempts from the same account, mismatched user details) and determine whether they are legitimate or fraudulent/suspicious.
Investigation & Case Management – Conduct detailed investigations into suspicious accounts or activities. Gather all relevant data (user profile, linked bank accounts, transaction history, device info, etc.) to build a case. Document your findings and conclusions in an organized manner. Decide on actions such as freezing transactions, suspending accounts pending verification, or reporting incidents.
Risk Rule & Model Tuning – Work with our data science and engineering team to refine the risk scoring models and business rules. Provide insight into the efficacy of current rules (false positives/negatives) and suggest new rules or thresholds based on your investigations. For example, you might notice a pattern of fraud that slips through and recommend a new rule to catch it. Test changes to risk logic in a sandbox environment and validate improvements.
KYC/Onboarding Oversight – Review the results of customer due diligence processes. Ensure that all new customers (businesses or individuals) have passed KYC checks, and any that trigger warnings (e.g., on watchlist/OFAC screenings or identity verification discrepancies) are given proper attention. Work with the Customer Success and Support teams to request additional documentation or clarification from customers when needed.
Compliance & Reporting – Ensure our risk management practices comply with relevant financial regulations and internal policies. Prepare reports or summaries of risk events and key risk indicators for management and potentially for regulatory audits or partner banks. If required, assist in filing any regulatory reports (such as Suspicious Activity Reports - SARs) in coordination with a compliance officer or legal counsel.
Fraud Prevention Strategy – Develop and continuously update our fraud prevention strategy. Stay informed about emerging fraud trends in the payments/banking industry (such as new phishing schemes, identity theft tactics, account takeover patterns). Adjust our internal strategies proactively to address these threats. This might involve proposing new verification steps, transaction limits, or partnering with external fraud prevention services.
Cross-Functional Collaboration – Collaborate with the Product Lead to incorporate risk considerations into product features (for instance, adding a step for high-risk users). Work with Customer Support and Success teams to handle fraud cases delicately when legitimate customers are affected (such as communicating why a transaction was flagged and what’s needed to resolve it). Educate the broader team on risk awareness and best practices.
Policy Development – Establish internal risk and compliance policies. This includes drafting standard operating procedures for risk investigations, defining escalation paths for severe cases, setting guidelines for when to block or allow transactions, and outlining the responsibilities and limits of various team members in the risk management process. Update these policies as the business and regulatory landscape evolves.
Team Leadership & Growth – As the lead, mentor any junior risk/compliance analysts as they come on board. Provide training on our systems and analytical methods. Set the tone for a risk-conscious culture. Manage the workload and case queue, ensuring investigations are completed thoroughly and timely. Plan for scaling the risk team in alignment with company growth.
Required Qualifications
Risk/Fraud Analysis Experience – 4+ years experience in a risk management, fraud analysis, or compliance analyst role within financial services or fintech. You should have hands-on experience monitoring transactions and investigating fraud or suspicious activities.
Knowledge of Financial Crimes – Strong understanding of common fraud schemes (ACH/wire fraud, identity theft, social engineering scams, etc.) and preventative controls. Familiar with AML concepts and regulations – you know the basics of KYC, OFAC sanctions screening, suspicious activity reporting, and have possibly worked under BSA/AML compliance programs.
Analytical Skills – Excellent analytical and critical thinking skills. Comfort working with data; able to interpret statistical outputs of risk models or analyze transaction datasets (using Excel, SQL, or analytics tools) to detect patterns. Detail-oriented in examining individual cases and conscientious in documentation.
Decision-Making – Ability to make swift but sound judgments on potentially ambiguous cases. Knack for assessing risk and deciding when to escalate or act conservatively. You can balance being thorough with being efficient to keep up with a fast-moving queue of alerts.
Tools & Systems – Experience with risk management and fraud detection tools or platforms (for example, third-party fraud detection systems, or in-house dashboards). Comfortable with the concept of risk scoring engines. If you’ve used case management systems or alert handling systems, that’s a plus. Some familiarity with SQL or data querying to pull investigation data is helpful.
Communication – Strong written and verbal communication skills, especially when documenting investigations or explaining risk decisions. Able to draft clear internal reports and also communicate findings or requirements to non-risk colleagues (or even external parties) in a concise manner.
Integrity & Compliance Mindset – High ethical standards. In a role dealing with sensitive financial information and decisions that can impact customers and compliance, integrity is paramount. You understand the importance of confidentiality and diligence.
Adaptability – Comfortable working in a startup where you may need to build processes from scratch. Able to adapt to new tools and changing fraud patterns quickly. Eager to take initiative and create structure in a fast-paced, resource-limited environment.
Bachelor’s Degree – in Finance, Business, Data Analytics, or related field; or equivalent work experience in risk management. Additional relevant certifications or training are welcome.
Preferred Qualifications
Fintech/Payments Background – Direct experience in a fintech startup or payments company’s risk/fraud team. Knowledge of the ACH network rules, credit card fraud mitigation, chargeback processes, and/or faster payment systems (RTP/FedNow) risk considerations.
Certifications – Professional certifications such as CAMS (Certified Anti-Money Laundering Specialist), CFE (Certified Fraud Examiner), or CFCS (Certified Financial Crime Specialist) which demonstrate formal training in financial crime detection and prevention.
SQL and Data Skills – Ability to write SQL queries to fetch specific data for investigations or to perform ad-hoc analyses of transaction trends. Experience using data analysis or visualization tools to report on risk KPIs (e.g., fraud rate, SAR filings, etc.).
Policy and Audit Experience – Experience writing or updating risk/compliance policies and participating in audits or regulatory examinations. Familiarity with what regulators or banking partners typically require from a payments company in terms of risk controls.
Use of Fraud Tech – Hands-on experience with modern fraud prevention technologies, such as device fingerprinting, behavior analytics, or machine-learning based risk scoring systems. Understanding their inputs and outputs can help in tuning our in-house systems.
Crisis Management – Experience handling incidents of significant fraud or data breaches, coordinating responses to minimize damage and remediate issues. Shows that you can perform under pressure and know how to communicate during crises.
Continuous Learning – Demonstrated interest in staying current on the latest in fintech fraud and AML news/trends, possibly via memberships in fraud prevention networks or attending relevant workshops/seminars.
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About the job
Job type
Full-Time, Hybrid
Salary
$100 - $125k
Benefit you’ll get
Flexible Work Environment – We offer hybrid and remote options so you can work where you’re most productive, whether that’s at home, in-office, or a mix of both.
Equity Ownership – As an early team member, you’ll receive equity in the form of options or RSUs—your contributions grow the company, and you share in the upside.
Unlimited PTO – Take the time you need to rest, recharge, or handle life outside of work. We trust our team to balance time off with results.
Health & Wellness Coverage – Comprehensive medical, dental, and vision plans help keep you and your family healthy, with 100% employee premium coverage on select plans.
Paid Parental Leave – We support growing families with fully paid time off for new parents, including adoption and foster care.
Professional Development – We invest in your growth with paid courses, certifications, and conference opportunities tailored to your role and interests.
Home Office & Equipment Stipend – Receive a stipend to set up your home workspace and get the tools you need to work comfortably and effectively.
Team Retreats – We host regular offsites to align on strategy, collaborate face-to-face, and have fun as a team.
Autonomy & Ownership – We give you space to lead initiatives, own outcomes, and shape the direction of your work without micromanagement.
Mission-Driven Work – Help build infrastructure that moves money more efficiently, securely, and transparently for modern businesses.
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Company Overview
Straddle is building the intelligence layer for modern payments, enabling smarter, faster, and more reliable financial decisions through data and machine learning. We operate at the intersection of fintech, data infrastructure, and real-time decisioning, where the models and insights we build directly impact transaction success, fraud prevention, and customer experience.
We are a fast-moving, high-ownership team that values speed, clarity, and pragmatic execution. We believe in delivering impact quickly, iterating continuously, and building systems that scale as the business grows.
Position Overview
We are seeking a Senior Data Science Product Manager to drive the discovery, scoping, and cross-functional orchestration of Straddle's data and ML-powered product capabilities.
This role bridges the gap between data science, product, and the market. You will work closely with product leadership to understand Straddle's product roadmap, identify where data and ML can create differentiated value, and translate those opportunities into well-scoped, high-impact data product initiatives. Examples include intelligent routing systems that maximize bank connection success across providers, balance prediction models that reduce payment failures and unlock new product offerings like guaranteed payments, and risk scoring features that shape how payment products are priced and rolled out.
Today, data product strategy and roadmap ownership sits with the Head of Data Science. As the team scales, this role will serve as the connective tissue between the data science team and the rest of the organization, engaging directly with customers, attending industry events, understanding the payments landscape, and channeling market needs back into the data product roadmap. You will drive discovery, scoping, and cross-functional coordination for data initiatives, and be a strong voice contributing to leadership's Data Roadmap and OKRs.
The ideal candidate is someone who thinks like a product manager but speaks the language of data science. Comfortable scoping an ML feature, challenging a model's assumptions, and presenting a data product strategy to leadership in the same week.
Essential Functions
Drive discovery, scoping, and cross-functional coordination for data science and ML initiatives that support Straddle's core payment products. Surface opportunities, write proposals, and keep projects on track in partnership with the Head of Data Science
Partner with product leadership to understand the full product landscape and identify where data-driven capabilities (models, features, scoring, intelligence) can create competitive advantage
Translate product and business needs into well-defined data science project briefs, including problem framing, success metrics, data requirements, and delivery milestones
Engage directly with customers, prospects, and partners to understand real-world payment challenges and surface opportunities for data products
Represent Straddle's data capabilities externally at industry events, fintech meetups, and partner conversations. Bring market intelligence back to the team
Collaborate with data science and engineering to ensure data products are built with the right trade-offs between speed, accuracy, and scalability
Identify data gaps where acquiring new data sources, improving data quality, or connecting to new providers can meaningfully improve product and model outcomes
Define and track success metrics for data products post-launch, driving iteration based on real-world performance
Manage intake and triage of cross-functional data requests, providing recommendations on prioritization to the Head of Data Science
Build and maintain PRDs and product proposals for data science initiatives, ensuring alignment across product, engineering, and leadership
Desired Experience & Skills
5+ years in product management, data science, or a hybrid data product role
Strong understanding of machine learning concepts. You don't need to build models, but you need to know what's feasible, what's hard, and what questions to ask
Demonstrated experience translating business problems into data/ML product requirements
Track record of shipping data-powered features or products in a B2B or fintech context
Strong product intuition. You understand user needs, market dynamics, and how to prioritize ruthlessly
Experience working directly with customers or in customer-facing contexts (sales engineering, solutions, product discovery)
Familiarity with payments, open banking, risk/fraud, or financial services is strongly preferred
Excellent communication skills. You can write a clear PRD, run a stakeholder review, and present to leadership with equal comfort
Comfort operating in ambiguity. You thrive when the problem isn't fully defined yet
Experience with data platforms (Databricks, SQL, analytics tools) is a plus
Technical Familiarity
Machine learning product lifecycle: problem framing, feature design, model evaluation, deployment, monitoring
Data infrastructure concepts: pipelines, feature stores, lakehouse architecture, data quality
Payment systems: ACH, RTP, open banking, identity verification, risk scoring
A/B testing and experimentation design
Analytics and BI tools (dashboards, cohort analysis, funnel metrics)
Familiarity with Linear, Notion, or similar product management tooling
Culture Fit
Speed over perfection — momentum creates opportunity; we deliver, iterate, and improve
Ownership mentality — we don't stop at "our part"; we ensure outcomes
Honest, data-driven thinking — we trust the data, even when it's inconvenient
Curiosity and creativity — we ask "why," explore ideas, and challenge assumptions
Pragmatic execution — we balance long-term scalability with immediate business impact
Collaborative mindset — we think out loud, share context, and make each other better
We are building systems that directly impact real financial outcomes. That responsibility demands high standards, strong judgment, and a bias toward action.


