Job Description
Associate LatentView Analytics - 3.8 Seattle, WA Job Details 3 hours ago Qualifications AI models Cloud analytics services Predictive modeling analysis Underwriting Financial model development Credit risk assessment NumPy Banking analysis in risk and credit Consumer lending analysis in risk and credit AI platforms (beyond public GPTs) Computational framework SQL Pandas Machine intelligence Supervised learning Matplotlib Seaborn Unsupervised learning Query management Model evaluation Machine learning frameworks Feature engineering Stakeholder relationship building Data analysis software Stakeholder management
Full Job Description Designation:
Associate. Level:
L2 Experience:
5 to 8 years Location:
Texas, Texas, United States. Job Description We are looking for an experienced and highly analytical Data Scientist to join our Risk Analytics team within the Merchant Cash Advance (MCA) and alternative lending domain. The ideal candidate should possess strong expertise in SQL, Python, Machine Learning, and statistical modeling, along with hands-on experience in risk analytics and financial data analysis. The candidate will work closely with underwriting, risk, collections, fraud, and business teams to develop scalable predictive models and analytical solutions that improve portfolio performance, reduce risk exposure, and support data-driven decision-making across the MCA lifecycle. This role requires a strong problem-solving mindset, deep analytical capability, and the ability to work with large and complex financial datasets in a fast-paced environment. Key Responsibilities Develop and deploy predictive models for MCA risk-related use cases including: Default prediction Risk scoring Fraud detection Renewal propensity Delinquency forecasting & Collections optimization Analyze merchant transaction data, repayment behavior, bank statements, and portfolio trends to identify business and risk insights. Build and optimize complex SQL queries for large-scale data extraction, transformation, and analysis. Design scalable data science workflows and analytical pipelines using Python. Perform exploratory data analysis (EDA), feature engineering, model training, validation, and monitoring. Collaborate with underwriting, credit risk, operations, and business stakeholders to translate business problems into analytical solutions. Evaluate model performance using statistical and machine learning metrics and continuously improve model accuracy and stability. Work with structured and semi-structured financial datasets from multiple internal and external data sources. Support portfolio monitoring and early warning systems for risk mitigation. Prepare dashboards, reports, and presentations for senior leadership and business stakeholders. Ensure analytical solutions align with regulatory, compliance, and business requirements. Required Skills & Qualifications Strong expertise in SQL including: Complex joins,Window functions, Query optimization, Data aggregation, Analytical querying, Strong programming skills in Python. Hands-on experience with Machine Learning algorithms and frameworks such as: Scikit-learn, XGBoost, MLFlow Strong understanding of: Supervised and unsupervised learning Classification and regression techniques Statistical analysis Feature engineering Model evaluation methodologies Experience with Python data libraries: Pandas, NumPy, Matplotlib, Seaborn Experience working with cloud and big data platforms such as AWS, Big Query and version control tool like Git Domain Expertise Strong experience in the Merchant Cash Advance (MCA), alternative lending, or financial risk analytics domain. Good understanding of:
Merchant underwriting, Credit risk assessment, ACH/payment bbehaviour, Revenue-based financing, Fraud analytics, Portfolio risk monitoring, Collections and repayment lifecycle Experience working with financial and transactional datasets. Analytical & Soft Skills Strong analytical thinking and quantitative problem-solving capability. Ability to interpret complex business problems and convert them into scalable analytical solutions. Excellent communication and stakeholder management skills. Ability to work independently and collaboratively across global teams. Strong attention to detail and data-driven decision-making mindset. Preferred Qualifications Experience in MCA, FinTech, or alternative lending organizations. Exposure to MLOps, model deployment, or productionization workflows. Experience with visualization tools such as: Power BI, Tableau, Familiarity with risk strategy development and portfolio analytics. Educational Qualification Bachelor's or Master's degree in: Computer Science / Data Science /Statistics/ Mathematics /Artificial Intelligence /Finance Analytics/ Engineering or related quantitative disciplines Ideal Candidate Profile We are looking for candidates who: Have strong hands-on experience in data science and risk analytics,Possess deep analytical and problem-solving capabilities, Understand MCA or alternative lending business processes, And can deliver scalable, business-driven analytical solutions in a fast-paced environment. Job Snapshot Updated Date 01-06-2026 Job ID J_5309 Location Seattle, Washington, United States Employee Type Permanent
