Data Scientist

EDGE ( is a B2B fintech on a mission to expand credit access for consumers historically unserved and underserved by the reports and scores of traditional credit bureaus. We’re doing this with risk analytics based on complementary alternative data that reveals a more complete financial picture.

Founded in 2021, Edge is part of a larger family of fintech brands that sits underneath our parent company, NinjaHoldings ( NinjaHoldings’ brands also include CreditNinja, a nationwide online consumer lending business established in 2017, and NinjaCard, a neobanking platform focused on consumers in the emerging credit space.

The EDGE business is at an inflection point where we’ve proven our platform’s value with early adopters and we’re ready to go full-throttle into our target markets. Elevating every aspect of our marketing efforts is a critical element in this planned ramp-up.

As part of our mission to make finance more accessible, we’re looking for a Data Scientist or Data Engineer to join our growing team.

In this role, you will apply expertise in data science and data engineering to build robust analytical models and end-to-end data services. You will develop and maintain ML pipelines, conduct data analyses to inform decisions, and implement scalable, high-performance backend systems in a cloud-native environment.

This is a unique opportunity to create powerful fintech solutions and directly impact product innovation.

Key Responsibilities:

Model Development and Data Analysis

• Design, train, and validate predictive models using advanced machine learning techniques
• Conduct exploratory data analysis and research to uncover trends and drive the development of new feature sets

Data Engineering and Services

• Develop, maintain, and optimize scalable data pipelines and workflows in Python
• Implement and manage containerized applications using Docker and Kubernetes
• Build and maintain gRPC and RESTful services to support real-time analytics and data delivery
• Leverage AWS (S3, RDS, EKS) and other cloud services to deploy and manage data solutions

Collaboration & Operations

• Work closely with front-of-house teams to translate requirements into data-driven features and services
• Partner with platform engineers to ensure efficient, reliable integration of analytics into production systems
• Employ best practices for version control (GitHub) and CI/CD pipelines to streamline deployment

Requirements:

• 2+ years in a Data Science, Data Engineering, or Software Engineering role
• Advanced Proficiency in Python (including Pandas, NumPy) and strong understanding of machine learning principles and workflows
• Experience building, maintaining, and optimizing data pipelines; familiarity with distributed/parallel processing
• Hands-on experience with AWS (S3, RDS, EKS) and container orchestration with Docker/Kubernetes
• Experience designing, implementing, and consuming gRPC and RESTful APIs
• Strong knowledge of relational databases (PostgreSQL or similar) and SQL

Additional Pluses, but not requirements:

• Experience with Kubeflow
• Experience with Clickhouse, Snowflake and other column-oriented databases
• Proficiency in Go or Rust, with application to data processing

Benefits:

• Competitive salary and benefits package
• Fun, fast-paced work environment
• Dynamic start-up culture
• Ability to make an immediate impact in a growth stage company
• Convenient downtown Chicago office located in the heart of the city
• Equal opportunity employer

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