Principle Predictive Analytics Consultant #1663

United States

Meridian Link

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The Principal Predictive Analytics Consultant will be a key member of the analytics team, responsible for leading the design and delivery of critical solutions like Automated Underwriting, Risk Scoring, and Portfolio Monitoring. This role involves utilizing advanced data science tools and techniques to provide analytics services that optimize decision engines and improve the lending operations of financial institutions. The position will focus on building, testing, and validating predictive and optimization models that support credit underwriting decisions. The consultant will develop data-driven solutions to enhance credit risk assessments, automate decision-making, and optimize underwriting processes.  The ideal candidate should possess a thorough understanding of loan origination systems, core underwriting practices, credit bureau data, and the interaction between these areas to drive predictive analytics. Additionally, they should have a strong grasp of how decisioning engines work in lending, banking, or credit union environments for consumer loans, including data integration and automated underwriting. • Data Management & Manipulation:- Take ownership of managing large, complex datasets from multiple sources, ensuring they are accurate, clean, and organized for analysis. Perform detailed data wrangling tasks to handle data inconsistencies to prepare data for use in predictive models and analysis.- Implement advanced data transformation techniques (e.g., feature engineering, aggregation, normalization) to optimize data for specific machine learning, optimization and statistical models.
• Predictive Model Development:- Work on various types of predictive models, including classification, regression, and clustering, using algorithms like decision trees, random forests, or neural networks.- Contribute to the fine-tuning of models by optimizing hyperparameters and evaluating performance using cross-validation, ensuring that models meet business and technical requirements.
• Data Science Project Execution:- Develop end-to-end analytical solutions, from data collection to model deployment, ensuring that the solutions meet the client's business objectives, such as improving lending strategies or underwriting decisions.- Ensure that the analytical results align with key performance indicators (KPIs) and help drive measurable outcomes.- Participate in the internal development of new data science methodologies that address evolving needs related to underwriting for our financial institution clients.
• Client Communication & Project Delivery:- Present complex analytical findings in a clear and actionable format to internal stakeholders and external clients helping them interpret the results of predictive models and make informed decisions based on data insights.- Proactively identify project risks and work closely with team members to mitigate them, ensuring that the final deliverables are of the highest quality, meet or exceed client expectations, and are delivered within the defined timelines.- Provide feedback and contribute to the continuous improvement of the data science workflow, ensuring projects are executed efficiently and with precision. Qualifications:
• Education & Experience: - Bachelor’s or Master’s degree in Statistics, Data Science, Analytics, Mathematics, Economics, Finance, or a related field is preferred- 5+   years of experience building and validating predictive credit risk models, preferably in the financial services or lending industry.- Strong background in credit risk and credit underwriting processes for consumer loans focused on Auto Lending, Personal Loans, and Credit Cards- Proven experience with model development, implementation, testing, validation, and monitoring.
• Technical Skills:- 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 Azure Machine Learning Services for training, building, and deploying models is preferred, along with experience in Azure Cloud Infrastructure and MLOps.
• Analytical Skills:- Strong understanding of credit risk factors and ability to identify key indicators for underwriting decisions.-Ability to translate complex data into actionable business insights and communicate them effectively to stakeholders.-Strong problem-solving skills and attention to detail in analyzing data and validating models.
• Key Competencies:-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.MeridianLink has a wonderful culture where people value the work they do and appreciate each other for their contributions. We develop our employees so they can grow professionally by preferring to promote from within. We have an open-door policy with direct access to executives; we want to hear your ideas and what you think. Our company believes that to be productive in the long term, we must have a genuine work-life balance. We understand that employees have families and full lives outside of the office. To that end, we honor their personal commitments.MeridianLink is an Equal Opportunity Employer. We do not discriminate based on race, religion, color, sex, age, national origin, disability, or any other characteristic protected by applicable law.  MeridianLink runs a comprehensive background check, credit check, and drug test as part of our offer process.Salary range of $114,300 - $161,400. [It is not typical for offers to be made at or near the top of the range.] The actual salary will be determined based on experience and other job-related factors permitted by law including geographical location.Meridianlink offers:
Potential For Equity-Based AwardsInsurance coverage (medical, dental, vision, life, and disability)Flexible paid time offPaid holidays401(k) plan with company matchRemote workAll compensation and benefits are subject to the terms and conditions of the underlying plans or programs, as applicable and as may be amended, terminated, or superseded from time to time.  #LI-REMOTE
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Tags: Azure Banking Classification Clustering Credit risk Data management Economics Engineering Feature engineering Finance KPIs Machine Learning Mathematics ML models MLOps Model deployment Pandas Python Scikit-learn SQL Statistics Testing

Perks/benefits: Career development Equity / stock options Health care

Regions: Remote/Anywhere North America
Country: United States

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