Senior Data Scientist

Title: Senior Data Scientist

Reports to: VP Credit Decision Sciences

Location: US Remote

About the Company 

At BMG Money, our mission is to provide access to affordable and responsible credit for underserved consumers facing unexpected expenses. We all share one vision— Redefining lending through technology, where underserved individuals can thrive financially through forward-thinking, responsible, and innovative financial solutions.

Job Summary

We are seeking an experienced and highly capable Data Scientist to join our team at BMG Money. This senior-level career role is crucial for transforming large, complex datasets into strategic insights that drive decision-making across various functions. The successful candidate will be responsible for independently developing, validating, and supporting the implementation of predictive models, machine learning algorithms, and advanced dashboards. This role requires strong technical mastery and the ability to work collaboratively to deliver high-impact solutions.

Key Responsibilities

• Develop, validate, and support the deployment of predictive models and machine learning algorithms, ensuring they meet rigorous standards for accuracy and business relevance.
• Collect, process, and analyze massive volumes of structured and unstructured data, providing technical expertise within key data domains.
• Design and deliver insightful dashboards, reports, and data visualizations for business, product, and technology stakeholders, clearly articulating findings and their implications.
• Proactively identify patterns, trends, and business opportunities hidden within the data, translating findings into proposed solutions and actionable analysis.
• Support other data-driven projects such as fraud detection and portfolio analysis.
• Ensure compliance with regulatory requirements and internal policies related to credit risk modeling.
• Collaborate closely with product, engineering, and business teams to integrate data-driven solutions into production systems.
• Ensure the quality, consistency, and integrity of all utilized datasets and contribute to establishing best practices for data quality.
• Mentor junior data analysts on best practices for data cleaning, modeling techniques, and analytical rigor.
• Research, evaluate, and apply new data analysis techniques, tools, and technologies (e.g., cloud platforms, new programming libraries).
• Stay current with the latest technological advancements in the Data Science field to recommend process and equipment improvements.
• Provide hands-on support and guidance to junior analysts, ensuring access to high-quality, well-structured data sources.
• Support the manager on all related matters, discussing complex issues and recommending well-researched solutions to inform procedural and strategic actions.

Qualifications

• Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field.
• Minimum of 4+ years of professional experience in data analysis, data modeling, and validation of analytical models in the financial services industry.
• Advanced SQL proficiency (writing complex, optimized queries) 
• Business Intelligence (BI) tools (e.g., Tableau, Power BI, Looker) 
• Advanced Statistical and Mathematical aptitude with experience in experiment design (e.g., A/B testing) 
• Advanced proficiency in Python or R and their data science ecosystems (e.g., Pandas, Scikit-learn). 
• Advanced Microsoft Excel
• Strong Critical Thinking and Analytical Skills • Demonstrated Decision-Making Capacity
• Excellent Communication and Presentation Skills (ability to present technical findings clearly to a business audience)
• Strong Organizational and Planning Skills
• Proven ability to work effectively in a team environment and mentor peers/junior staff.

Preferred Qualifications

• Master’s degree or post-graduate specialization in a relevant field.
• Experience with Credit Risk Management. Prior experience contributing to model deployment/MLOps processes.
• Advanced English proficiency (for documentation/global teams). Familiarity with cloud platforms (AWS, Azure, or GCP).
• Foundational understanding of credit risk management