AI / ML Data Scientist
With 30 years at the forefront of fintech innovation, we specialize in SaaS lending solutions that lead the industry. Our core mission is customer-centric, focusing on empowering Credit Unions across the United States with the tools to offer accessible, competitive lending services.
We are deeply committed to enhancing the financial ecosystem for a broad network of credit unions, members and auto dealers. We invest in our greatest assets, our employees, and foster a culture of innovation and ownership through freedom and responsibility. We celebrate fiscal accountability, operational rigor and efficiency to create a sustainably healthy and robust business for the long term.
The successful candidate will design and deploy advanced ML models, implement AI-driven automation across our lending processes, and spearhead the integration of generative AI technologies to enhance our digital lending solutions for credit unions and community banks.
This role offers the opportunity to work at the forefront of AI in fintech, building production-scale machine learning systems that process millions of lending decisions while exploring emerging AI technologies like large language models and computer vision for document processing.
AI / ML Model Development & Deployment
- Design, develop, and deploy advanced machine learning models for real-time credit decisioning, and document processing.
- Build and optimize neural networks for fraud detection, loan default prediction, and customer lifetime value modeling using TensorFlow, PyTorch, or similar frameworks
- Implement automated machine learning (AutoML) pipelines to streamline model development and hyperparameter optimization
- Create natural language processing solutions for loan application analysis, customer service automation, and regulatory compliance monitoring
AI Infrastructure & MLOps
Build and maintain scalable ML infrastructure using cloud platforms (Primarily Azure, but can extend to AWS, GCP)Implement MLOps best practices including model versioning, continuous integration / deployment, and automated monitoringDevelop A / B testing frameworks for ML models to measure performance and business impact in productionCreate automated model retraining pipelines and drift detection systemsGenerative AI & Emerging Technologies
Research and implement generative AI applications for loan document processing, customer communication, and risk assessment reportingDevelop retrieval-augmented generation (RAG) systems for intelligent customer support and regulatory compliance assistanceExplore large language model fine-tuning for financial domain-specific applicationsInvestigate federated learning approaches for privacy-preserving model training across multiple financial institutionsCollaboration & Communication
Create data visualizations, dashboards, and reports to communicate findings to product teams, risk management, and executive leadershipCollaborate with cross-functional teams including product development, risk management, and engineering to define analytical requirements and KPIs for lending productsPresent complex financial analyses to diverse stakeholders, translating technical findings into business-actionable insightsExperimentation & Optimization
Design and conduct A / B tests to optimize loan application processes, approval rates, and customer experience across Origence's digital lending platformImplement statistical testing methodologies to measure the impact of product changes and business initiativesContinuously monitor and improve model performance and accuracyThe Ideal Candidate
Education : Master's degree or PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, or related technical field
Experience : 4+ years of hands-on experience developing and deploying ML models in production environments, preferably in financial services or fintech
Proven track record of building end-to-end ML systems from research to production deployment
Experience with both supervised and unsupervised learning techniques, deep learning, and reinforcement learning
Technical Skills
Expert-level proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn, XGBoost, LightGBM)Strong experience with cloud ML platforms (Primarily Azure, but can extend to AWS, GCP)Proficiency in MLOps tools and practices (MLflow, CI / CD for ML)Experience with big data technologies (Spark, Kafka, Airflow) and distributed computingKnowledge of SQL, NoSQL databases, and data engineering principlesFamiliarity with model interpretation techniques (SHAP, LIME) and explainable AI methodsAI / ML Specializations
Experience with transformer architectures, attention mechanisms, and large language modelsKnowledge of computer vision techniques for document processing and image analysisUnderstanding of natural language processing, text mining, and sentiment analysisFamiliarity with generative AI models (GANs, VAEs, diffusion models)Experience with time series forecasting and sequential modeling techniquesDomain Knowledge
Understanding of loan origination principles and lending industry metricsKnowledge of common financial ratios, loan performance indicators, and risk assessment methodologiesAwareness of regulatory environment affecting consumer and commercial lendingPreferred Qualifications
Advanced AI / ML Experience
PhD in Machine Learning, AI, or related field with publications in top-tier conferences (NeurIPS, ICML, ICLR, etc.)6+ years of experience building production ML systems at scale in fintech, banking, or related regulated industriesExperience leading AI research initiatives or managing ML engineering teamsTrack record of patents or open-source contributions in AI / MLCutting-Edge AI Technologies
Hands-on experience with foundation models, prompt engineering, and LLM fine-tuning (GPT, BERT, T5, etc.)Knowledge of multi-modal AI systems combining text, vision, and structured dataExperience with federated learning, differential privacy, and privacy-preserving ML techniquesFamiliarity with quantum machine learning or neuromorphic computing approachesUnderstanding of AI ethics, bias detection, and fairness in ML systemsTechnical Leadership
Experience with MLOps at enterprise scale, including model governance and risk managementKnowledge of edge AI deployment and model optimization for mobile / embedded systemsBackground in distributed training, model parallelism, and large-scale inference systemsFamiliarity with AI accelerators (GPUs, TPUs, specialized AI chips) and performance optimizationWhy You Should Apply
Flexible Working EnvironmentPaid Time Off401k (8% match)College Tuition Benefits / Tuition ReimbursementGood Benefits optionsCompany Culture! Cultural and Holiday celebrations, Theme days like Star Wars Day & Bring your Kids to Work Day, Monthly Townhalls and Quarterly Company Meetings that ensure awareness, inclusion, and transparency.The starting salary range for this full-time position in Irvine, CA is $147900 - $184900 per year. This base pay will take into consideration internal equity, candidate's geographic region, job-related knowledge and experience among other factors. Origence maintains a highly competitive compensation program. Under company guidelines, this position is eligible for an annual bonus to provide an incentive to achieve targeted goals. Bonuses are awarded at company's discretion on an individual basis.
Origence is an equal opportunity employer. All recruitment, hiring, training, compensation, benefits, discipline, and other terms and conditions of employment will be based upon an individuals' qualifications regardless of race, religion, color, sex, gender identity, sexual orientation, national origin, ancestry, military service, marital status, pregnancy, age, protected medical condition, genetic information, disability or any other category protected by federal, state or local law.
