Lead and mentor a team of quantitative professionals while personally executing rigorous validations of machine learning models for underwriting and credit risk.
Evaluate conceptual soundness, data integrity, and performance stability through comprehensive testing, in-depth reviews, and continuous monitoring.
Collaborate with cross-functional stakeholders to enhance the enterprise-wide Model Risk Management framework and ensure compliance with internal and regulatory standards.
Affirm is a financial technology company that provides buy now, pay later services without hidden fees or compounding interest. It is a publicly traded, remote-first company with a large workforce and a culture focused on innovation, risk management, and putting people first.
Conduct rigorous, independent validations of sophisticated credit/fraud models, including machine learning and traditional statistical models.
Develop automated, independent monitoring suites in Python to track KRI/KPI drift, population stability, and feature importance shifts in real-time.
Partner with model developers to drive remediation of validation findings and ensure models are mathematically robust and compliant.
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without hidden fees or compounding interest. The company is a remote-first firm with a focus on competitive benefits and an inclusive culture.
Build and deploy machine learning models for credit and fraud risk management.
Collaborate with engineering to deploy models into production and analyze portfolio performance.
Communicate findings to stakeholders and develop internal tools for data science productivity.
Prosper is a fintech company that offers personal loans and credit cards through a digital marketplace. They have helped over 2 million customers and emphasize a collaborative, inclusive culture with flexible work options.
Identify, assess, and monitor risks associated with AI, machine learning, and generative AI across the organization.
Support AI governance, risk monitoring, and control evaluation to ensure responsible adoption of emerging technologies.
Collaborate with cross-functional teams to translate complex AI risks into actionable business insights.
BECU is a financial cooperative serving 1.5 million members with over $30 billion in assets. With a people-helping-people philosophy since 1935, the organization fosters a purpose-driven, collaborative culture focused on technology transformation and community impact.
Assess AI-enabled systems against regulatory requirements, standards, and conformity criteria.
Support clients and internal teams with AI/ML expertise and practical guidance.
Develop methodologies, tools, and training for AI conformity assessment.
This company focuses on the assessment of AI-enabled products and software across regulated industries, including medical devices and robotics. They operate in a global, multidisciplinary environment with a culture centered on trust, safety, and responsible AI adoption.
Design and implement AI systems for complex workflows, including multi-step reasoning and decision making.
Lead systematic experimentation and evaluation of agentic systems.
Finetune and adapt small and medium-sized foundation models for enterprise workloads.
Uniphore is a B2B AI-native company that builds a multimodal AI platform for enterprises, combining Generative AI, Knowledge AI, and automation. It is one of the largest companies in its space, with a culture focused on innovation and customer success.
Design and implement security controls and governance frameworks for AI and machine learning systems.
Develop threat models and security architectures tailored to LLMs, AI applications, and training data pipelines.
Identify and mitigate AI-specific risks like prompt injection, model abuse, and data exfiltration.
Jobgether is a platform that uses AI-powered matching to connect candidates with job opportunities. They operate as a technology-focused company with a remote team, emphasizing fair and efficient hiring processes.
Lead, grow, and develop a team of 3+ data scientists and governance professionals.
Own the fundamentals of model governance: performance monitoring, drift monitoring, fair lending assessments, validation, and more.
Set the strategy for the function, including automation, standardization, and customer relationships.
SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. They are a rapidly growing company backed by world-class investors, with offices across the US and India.
Partner with cross-functional teams to optimize risk operations and improve workflows.
Analyze operational data to identify trends, risks, and opportunities for process improvement.
Leverage AI tools and automation to enhance decision-making and efficiency.
The company operates in the technology sector, focusing on risk management and compliance. It maintains a supportive culture that values innovation, continuous learning, and operational excellence.
Build end-to-end Machine Learning pipelines, including data preparation, code optimization, automated model training, and prediction workflows.
Provide technical leadership in MLOps processes, establishing best practices for development, deployment, and maintenance.
Design and implement cloud-based architectures for AI and data solutions using platforms such as GCP, AWS, or Azure.
A technology company specializing in data-driven solutions for consumers, leveraging AI and cloud technologies to transform data into insights. The company fosters a dynamic, innovation-driven culture with a remote-first approach, collaborating across multidisciplinary teams.
Develop underwriting strategies for the assigned loan portfolio to improve performance and achieve business objectives.
Build dashboards and automate complex queries to monitor portfolio performance and enhance credit risk insights.
Interface with the Modeling/Scoring team to deploy risk strategies based on new models and improve deployment effectiveness.
Attain Finance brings over 50 years of expertise in providing credit solutions across the U.S. and Canada. They are a leading consumer credit lender with a portfolio including brands like Cash Money, LendDirect, and Heights Finance.
Design and deliver production-ready AI solutions including machine learning, generative AI, and LLM applications.
Translate complex business needs into scalable technical architectures and implementation plans.
Guide clients and cross-functional teams through discovery, architecture, and adoption of AI systems.
This company partners with organizations to deliver AI and data transformation solutions. It fosters a collaborative, remote-first culture focused on innovation, inclusivity, and meaningful impact.
Develop and implement enterprise Data and AI Governance frameworks, policies, and standards.
Establish risk-based governance processes for AI use cases across their lifecycle.
Partner with cross-functional teams to embed governance into development and change management.
Mercury is a fintech company that provides banking services through partnerships with FDIC-insured banks. It is an Equal Employment Opportunity employer that values diversity and belonging.
North America
Unlimited PTO
12w maternity
8w paternity
Lead state-of-the-art research and development in AI/ML, advanced statistical modeling, and applied mathematics to solve security problems.
Develop novel AI workflows and models to address Ent's security challenges, incorporating and advancing current SOTA approaches.
Collaborate with the team to invent frameworks and theoretical grounding while thinking outside the box to combine multiple techniques.
Ent is an intent-aware workspace security platform that secures human and AI-driven work by understanding intent and intervening at the moment of risk. Founded by former RiskIQ co-founders, backed by leading VCs, and in production with Global 2000 customers, the company values a customer-first, humble, and urgent culture.
Build, evaluate, and maintain underwriting and decisioning models that determine customer approvals and terms.
Design and run experiments to evaluate model performance and measure impact on approval rates and loss.
Collaborate with Product, Engineering, Legal, Compliance, and Operations to ensure systems reflect business goals and regulatory expectations.
FloatMe is a fintech company that builds underwriting and decisioning systems to determine customer approvals and terms. It operates as a fast-moving, high-standard team focused on rigorous ML work.
Build the data and model layer for an AI-enabled decision-support system, including ingestion, record matching, scoring, and generation.
Implement probabilistic matching, calibration, and retrieval-augmented generation in a controlled environment.
Ensure traceability, audit trails, and documentation for all data and model outputs.
DEFCON AI leverages AI, mathematical optimization, and data analytics for resilient optimization of complex systems. The team operates in a fully remote, results-based environment with a focus on innovation and collaboration.
Perform independent validation of financial and analytics quantitative models, including ALM, loss forecasting, and decision-support analytics.
Lead end-to-end validation engagements on high-complexity, high-criticality models to identify weaknesses and improvements.
Collaborate with model owners and stakeholders across Finance, Quantitative Research, and Growth Analytics to strengthen model governance.
Affirm is a financial technology company that provides buy now, pay later services without hidden fees or compounding interest. It is a publicly traded company with a remote-first culture and a focus on transparency and customer empowerment.
Design, build, and deploy machine learning models for cybersecurity use cases like threat detection and risk scoring.
Own the full model lifecycle from data preparation to production deployment, working closely with engineering and product teams.
Build preprocessing and feature engineering pipelines, and monitor model performance with continuous improvement.
SpyCloud transforms recaptured darknet data to disrupt cybercrime. With over 250 employees, it is home to cybersecurity experts protecting businesses and consumers from stolen identity data.
Design and implement security controls for AI applications, LLMs, and ML infrastructure.
Develop threat models, incident response, and red-team exercises for AI-specific attacks.
Collaborate with engineering and data science teams to embed security throughout the AI lifecycle.
They secure AI and machine learning systems against advanced threats, including prompt injection and adversarial attacks. This collaborative, inclusive technology firm offers significant career growth opportunities.