Senior Consultant, Financial Services Model Development and Risk Analytics

Location: Remote, United States
Work Model: Fully remote, supporting Eastern Time business hours
Job Type: Contract-to-hire
Duration: Initial six-month contract with potential conversion to client employment
Hours: 40 hours per week
Travel: Rare travel to New York may be requested

Overview

We are seeking a Senior Consultant with experience in Python, quantitative model development, data analysis, and financial services risk or compliance. This fully remote consulting opportunity will support a commercial financial services client in the development, analysis, testing, validation, and enhancement of data-driven models and related analytical processes.
The ideal candidate combines hands-on Python programming with experience analyzing complex financial datasets and supporting quantitative or statistical models. Candidates should also understand how models operate within a financial services risk, compliance, governance, or regulatory environment.
This is an analytical model-development position rather than a Python web application development role. The strongest candidates will have personally developed, tested, implemented, evaluated, or validated quantitative models and will be able to explain their individual responsibilities, methodologies, data preparation, and model-performance results.

Responsibilities

• Use Python to manipulate, analyze, clean, transform, reconcile, and evaluate large or complex datasets.
• Support the development, enhancement, testing, validation, and implementation of quantitative, statistical, risk, or analytical models.
• Perform exploratory data analysis to identify trends, anomalies, relationships, data-quality concerns, and potential model issues.
• Review model inputs, assumptions, methodologies, outputs, limitations, and underlying data quality.
• Develop reusable Python code, analytical routines, and data-processing workflows.
• Prepare data for modeling through activities such as data cleaning, transformation, reconciliation, aggregation, and feature engineering.
• Evaluate model performance using appropriate statistical, quantitative, or business-specific metrics.
• Assist with model documentation, methodology documentation, testing results, assumptions, limitations, controls, and supporting analysis.
• Support model governance, model validation, risk management, compliance, internal-control, or regulatory activities.
• Work with business, risk, compliance, data, and technical stakeholders to understand requirements and translate them into analytical solutions.
• Clearly communicate analytical findings, model behavior, data limitations, and technical concepts to both technical and nontechnical stakeholders.
• Work independently in a consulting environment and manage assigned deliverables against project deadlines.

Required Qualifications

• Three to five years of relevant professional experience in quantitative analytics, data science, quantitative model development, model validation, financial risk analytics, or a closely related discipline.
• Strong hands-on Python programming and analytical experience.
• Experience manipulating, analyzing, cleaning, and transforming large or complex datasets.
• Experience developing, testing, implementing, enhancing, or evaluating quantitative or statistical models.
• Ability to explain personal responsibility for model development, testing, validation, or implementation.
• Experience within banking, financial services, fintech, insurance, or another highly regulated financial environment.
• Exposure to risk management, compliance, model governance, model validation, regulatory requirements, audit controls, or a related control function.
• Understanding of model inputs, assumptions, methodologies, outputs, limitations, and performance measures.
• Strong analytical, quantitative, and problem-solving skills.
• Strong written and verbal communication skills.
• Ability to work independently and collaborate with business and technical stakeholders in a consulting environment.
• Ability to work remotely while supporting Eastern Time business hours.

Preferred Qualifications

• Bachelor’s or master’s degree in Statistics, Mathematics, Economics, Finance, Computer Science, Data Science, Engineering, or another quantitative discipline.
• Hands-on experience with Python libraries such as pandas, NumPy, scikit-learn, statsmodels, PySpark, or similar analytical and modeling tools.
• Experience using SQL to extract, reconcile, transform, and analyze financial or risk-related data.
• Knowledge of statistical modeling, forecasting, regression analysis, classification, machine learning, anomaly detection, or other quantitative techniques.
• Experience with model testing, backtesting, validation, performance monitoring, calibration, or threshold analysis.
• Familiarity with model-performance measures such as precision, recall, F1 score, false-positive rate, ROC-AUC, lift, calibration, RMSE, MAE, or comparable business-specific metrics.
• Experience documenting model methodology, assumptions, limitations, data lineage, controls, validation results, or monitoring procedures.
• Familiarity with financial services risk, regulatory, compliance, or model governance environments.
• Experience supporting credit risk, fraud, financial crime, AML, KYC, sanctions, fair lending, regulatory reporting, or another financial risk or compliance function.
• Consulting experience supporting banking, fintech, insurance, or other financial services clients.

System One, and its subsidiaries including Mountain Ltd., are leaders in delivering outsourced services and workforce solutions across North America. We help clients get work done more efficiently and economically, without compromising quality. System One not only serves as a valued partner for our clients, but we offer eligible employees health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, voluntary plans, as well as participation in a 401(k) plan.

System One is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, age, national origin, disability, family care or medical leave status, genetic information, veteran status, marital status, or any other characteristic protected by applicable federal, state, or local law.

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