Data Scientist

Company Description:

Essential Lending is a fast-growing, analytics-driven financial services company specializing in two primary areas:

1. Short-term personal loans (Wise Loan)
2. Portfolio servicing, including predictive modeling, data-driven credit policy development, loan origination, and customer service (The Analytics Solutions).

Headquartered in Fort Worth, Texas, our reach is global with a satellite call center in the Philippines and a diverse team of 40+ employees across Mexico, Brazil, the Dominican Republic, and India.

Company Culture

At Essential Lending, our values aren’t just words, they guide every decision and interaction:

• Be a Transparent Advocate – Advocate for what is best for each other and the customer. Listen with curiosity, speak with candor, act with compassion.
• If you feel good about working here, you’re doing it right!
• Make Gratitude an Attitude – Embody gratitude by being humble, attentive, clear and empathetic, focusing conversations on positive outcomes.
• Look Beyond; Follow Through – Be diligently committed, care deeply about your work, do more, learn more, take responsibility, and be self-motivated.

Position Overview

The Data Scientist will perform highly quantitative, data-driven analysis and make recommendations regarding how we should operate our business more effectively. While technical proficiency such as manipulating data with SQL and understanding predictive modeling techniques like logistic regression are necessary, the ideal candidate will have an aptitude for problem solving and business acumen.

Key Responsibilities

Lead Generation & Data Pipeline

• Manage a multi-stage lead evaluation process that screens large volumes of applications using progressively richer data sources.
• Incorporate diverse data sources, ranging from basic application information to third-party datasets and premium external data, to progressively refine lead evaluation.
• Leverage historical data and proprietary features to improve accuracy and decision-making.
• Ensure that data flows seamlessly across stages, feeding into final optimization models that balance acquisition costs, lead quality, and overall profitability.

Predictive Modeling & Optimization

• Build, refine, and maintain multiple underwriting and conversion rate models.
• Manage and improve an integer programming optimization model that balances lead acquisition cost with loan volume and profitability.
• Analyze lost bid data to refine bidding strategies and forecast incremental volume under different bid scenarios.

Data Engineering & Analytics

• Work with SQL and Python to transform, analyze, and productionalize datasets.
• Create, maintain, and validate proprietary derived features from internal lead history (e.g., repeat applicant tracking, identity cross-checking, inquiry frequency).
• Partner with marketing and finance teams to ensure models align with business objectives and compliance standards.

Portfolio Performance Analysis

• Conduct profitability analysis across loan cohorts and underwriting score ranges.
• Evaluate long-term loan repayment performance relative to predictive models.
• Provide actionable insights to optimize acquisition spend while maintaining credit quality.

Must haves:

• 4+ years of experience in data science, including building and testing predictive models.
• Proficient in T-SQL for data querying and transformation, and Python for modeling and analysis.
• 2+ years of experience in consumer lending, credit risk, or portfolio analysis.
• Strong analytical and problem-solving skills, able to combine statistics with business decisions.
• Clear communicator, able to explain technical results in business terms.

Nice to haves:

• Experience in affiliate marketing analytics or large-scale lead generation environments.
• Familiarity with third-party credit, banking, and fraud data sources.
• Exposure to profitability optimization in acquisition or marketing contexts.
• Experience with integer programming / mathematical optimization techniques.