About the job
About Us:
At ClarityPay, we empower businesses and their customers by effectively addressing intricate credit challenges with precision, speed, and intelligence. Leveraging our deep expertise and cutting-edge technology, we simplify the customer experience and achieve superior outcomes consistently.
As a rapidly expanding fintech company, we provide enterprise merchants with innovative pay-over-time solutions, including point-of-sale financing and integrated loyalty offers. Our mission is to create adaptable credit tools that enable businesses to cater to a broader customer base.
We prioritize teamwork, clarity of purpose, and meticulous attention to data to drive impactful actions. Our commitment to balancing speed with excellence ensures we deliver an outstanding customer experience.
Role Overview:
ClarityPay is embarking on a transformative journey to enhance our data strategy, technology stack, and data products. We seek a dynamic Head of Data Strategy to architect and realize our vision for the future.
This is an active, hands-on leadership role. Our existing data infrastructure demands significant improvement to meet our growth needs. We need an innovative leader who is as comfortable writing code as they are in shaping strategic direction. You will spearhead the transition from outdated systems to a modern, scalable AWS architecture, establishing robust data governance, MLOps, and AIOps frameworks that will propel us toward a data-driven operational model.
You will play a pivotal role in our thriving business, overseeing the entire data lifecycle, from ingestion to insight and automated decision-making.
Key Responsibilities:
Data Strategy & Transformation: Develop and implement a comprehensive roadmap to modernize our data architecture, guiding our shift from legacy systems to a state-of-the-art cloud environment that supports high-scale analytics and real-time ML inference.
Infrastructure Engineering (Hands-on): Design and deploy a robust data lakehouse solution utilizing the AWS ecosystem (S3, Glue, Redshift/Athena) and potentially incorporate Databricks, ensuring clean, reliable, and scalable data pipelines.
MLOps & AIOps Leadership: Create the infrastructure for our machine learning models. You will architect CI/CD pipelines for machine learning (utilizing tools like SageMaker), ensuring smooth deployment, monitoring, and retraining of our underwriting and operational models.
