Predictive Analytics Consultant
MeridianLink · United States
- Hybrid
- Full-time
- $120,000 / year
- United States
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Job highlights
- Lead design of underwriting and risk scoring solutions.
- Utilize advanced data science for lending optimization.
- Build, test, and deploy predictive credit risk models.
- Develop data-driven solutions for credit decisioning.
- Present findings to stakeholders for informed decisions.
About the role
Predictive Analytics Consultant
MeridianLink is seeking a Predictive Analytics Consultant to join our analytics team. This role is crucial for designing and delivering advanced solutions such as Automated Underwriting, Risk Scoring, and Portfolio Monitoring. You will leverage cutting-edge data science tools and techniques to offer analytics services that optimize decision engines and enhance the lending operations of financial institutions. The primary focus will be on building, testing, validating, and deploying predictive and optimization models to support credit underwriting decisions. You will develop data-driven solutions to improve credit risk assessments, automate decision-making, and streamline underwriting processes. We are looking for candidates with a deep understanding of loan origination systems, core underwriting practices, credit bureau data, and their interplay in driving predictive analytics. A strong grasp of decisioning engines in lending, banking, or credit union environments for consumer loans, including data integration and automated underwriting, is essential.Responsibilities
- Manage large, complex datasets from multiple sources, ensuring accuracy, cleanliness, and organization for analysis.
- Perform detailed data wrangling to handle inconsistencies and prepare data for predictive models and analysis.
- Implement advanced data transformation techniques (e.g., feature engineering, aggregation, normalization) to optimize data for machine learning, optimization, and statistical models.
- Develop and work with various predictive models, including classification, regression, and clustering, using algorithms like decision trees, random forests, or neural networks.
- Fine-tune models by optimizing hyperparameters and evaluating performance using cross-validation to meet business and technical requirements.
- Develop end-to-end analytical solutions, from data collection to model deployment, ensuring alignment with client business objectives like improving lending strategies or underwriting decisions.
- Ensure analytical results align with key performance indicators (KPIs) and drive measurable outcomes.
- Participate in the internal development of new data science methodologies to address evolving needs for our financial institution clients.
- Present complex analytical findings clearly and actionably to internal stakeholders and external clients, aiding their interpretation of predictive model results and data-driven decision-making.
- Provide feedback and contribute to the continuous improvement of the data science workflow, ensuring efficient and precise project execution.
Qualifications
- Bachelor’s or Master’s degree in Statistics, Data Science, Analytics, Mathematics, Economics, Finance, or a related field is preferred.
- 4+ years of experience building and validating predictive credit risk models, preferably in the financial services or lending industry.
- Proven experience with model development and deployment, testing, validation, and monitoring.
- Expert-level skills in programming languages such as Python for model development and analysis, leveraging Pandas, Scikit-learn, and other data handling, statistical, optimization, and machine learning frameworks.
- High-level proficiency and advanced skills in SQL for data querying and data manipulation.
- Proficiency in AWS for training, building, and deploying models is preferred, along with experience in MLOps.
- Strong problem-solving skills and attention to detail in analyzing data and validating models.
- Excellent communication skills to present technical concepts to non-technical stakeholders.
- Ability to work independently and as part of a team in a fast-paced, dynamic environment.
- Strong project management skills with the ability to handle multiple tasks and deadlines.
Key skills/competency
- Predictive Analytics
- Data Science
- Machine Learning
- Credit Risk Models
- Python
- SQL
- AWS
- MLOps
- Data Wrangling
- Financial Services
Skills & topics
- Predictive Analytics
- Data Science
- Machine Learning
- Credit Risk
- Python
- SQL
- AWS
- MLOps
- Financial Services
- Underwriting
- Consultant
- Analytics
How to get hired
- Tailor your resume: Highlight experience with predictive credit risk models, Python, SQL, and AWS, specifically for financial services.
- Showcase your expertise: Emphasize your ability to manage large datasets, perform data wrangling, and deploy machine learning models.
- Quantify your achievements: Use metrics to demonstrate the impact of your analytical solutions on lending operations and decision engines.
- Prepare for technical interviews: Be ready to discuss your experience with model validation, MLOps, and presenting complex data insights.
- Understand MeridianLink's focus: Research their solutions for automated underwriting and risk scoring in the lending industry.
Technical preparation
Practice Python with Pandas and Scikit-learn.,Refine SQL for complex data querying.,Build and validate credit risk models.,Study AWS and MLOps principles.
Behavioral questions
Describe a complex data problem solved.,How do you handle data inconsistencies?,Explain a model to non-technical people.,How do you manage multiple project deadlines?
Frequently asked questions
- What specific data science methodologies are used for the Predictive Analytics Consultant role at MeridianLink?
- The Predictive Analytics Consultant role at MeridianLink involves utilizing a range of methodologies including classification, regression, and clustering algorithms. You'll be expected to work with techniques like decision trees, random forests, and neural networks, with a strong emphasis on feature engineering, hyperparameter tuning, and model validation for credit risk assessment.
- How important is experience with loan origination systems for this Predictive Analytics Consultant position?
- Experience with loan origination systems is highly important for this Predictive Analytics Consultant role. A thorough understanding of these systems, core underwriting practices, and credit bureau data is essential for developing effective predictive analytics solutions that optimize lending operations.
- What level of Python proficiency is required for the Predictive Analytics Consultant at MeridianLink?
- Expert-level skills in Python are required for the Predictive Analytics Consultant position. This includes proficiency in using libraries such as Pandas and Scikit-learn for data handling, statistical analysis, optimization, and machine learning model development.
- Does MeridianLink prefer candidates with AWS experience for their Predictive Analytics Consultant role?
- Yes, proficiency in AWS for training, building, and deploying models is preferred for the Predictive Analytics Consultant role. Experience with MLOps practices is also a valuable asset for candidates applying for this position.
- What are the typical career growth opportunities for a Predictive Analytics Consultant at MeridianLink?
- MeridianLink encourages continuous improvement and offers opportunities to develop new data science methodologies. As a Predictive Analytics Consultant, you can grow by leading more complex projects, specializing in specific areas of analytics, and contributing to the advancement of the company's data science capabilities.
- How does MeridianLink ensure that analytical results align with business objectives for their clients?
- MeridianLink ensures analytical results align with business objectives by focusing on key performance indicators (KPIs) and driving measurable outcomes. The Predictive Analytics Consultant will develop solutions designed to improve lending strategies and underwriting decisions, directly contributing to client success.