Principal Data Scientist

Job Description

Sezzle is seeking a Principal Data Scientist to design, develop, and deploy machine learning models that enhance their financial platform. The role involves driving the creation of scalable machine learning solutions for personalized recommendations, fraud detection, and credit risk assessment. The Principal Data Scientist will blend machine learning development and operations (MLOps) to automate and optimize the full lifecycle of ML models. They will collaborate with engineers and data scientists to build large-scale solutions.Responsibilities include:

• Designing, building, and maintaining scalable ML infrastructure on AWS.
• Collaborating with product teams to develop MVPs for AI-driven features.
• Developing monitoring & alerting frameworks for machine learning models.
• Supporting cross-departmental AI utilization.
• Providing production support for machine learning models.
• Scaling ML architecture to support rapid user growth.
• Mentoring and elevating team skills.
• Staying updated with the latest advancements in machine learning technologies and AWS services.

Minimum requirements include:

• Bachelor's degree in a relevant technical field or equivalent experience.
• At least 6+ years of experience in machine learning engineering.

Ideal skills and experience include:

• Deep expertise in machine learning, recommendation systems, or related fields.
• Proven track record of developing machine learning models from inception to business impact.
• Proficiency with Python, and experience with Golang is a plus.
• Demonstrated technical leadership in guiding teams and owning end-to-end projects.
• Experience working with relational databases and data warehouses.
• Strong familiarity with AWS cloud services.
• Knowledgeable in Kubernetes, Docker, and CI/CD pipelines.
• Comfortable with monitoring and observability tools tailored for machine learning models.
• Solid foundation in data processing and pipeline frameworks.

Sezzle offers:

• A dynamic, fast-paced environment with opportunities for career advancement.