We are looking for a highly skilled and experienced Data Scientist to join our Common Data Model (CDM) team within the Data Science and Credit Risk function. This role is pivotal in ensuring the integrity, scalability, and performance of our credit risk models by developing, maintaining, and quality-controlling the input mapping and data rollup logic that powers our decisioning infrastructure. As a senior member of the team, you will lead a small team of data scientists and collaborate closely with engineering, product, and integration teams to translate various data sources into standardized features used in risk models and strategies. Responsibilities Own the design, development, and maintenance input mapper and rollup logic for credit bureau, core banking, internal datasets and any additional data sources in the future. Ensure accuracy, performance, and compliance through rigorous QC frameworks and automated validation tools. Collaborate with credit risk, product, engineering, and integration teams to deploy and support model and strategy features in production environments. Analyse complex datasets and derive accurate business logic in alignment with credit policy and model requirements. Lead and mentor a team of data scientists and analysts, ensuring adherence to best practices in software engineering and data science. Contribute to data governance, documentation, and version control of the CDM and associated tooling. Skills & Competencies 5+ years of experience in Data Science/Data Engineering/Analytics Strong Python skills ability to writing clean, testable, modular, and production-grade code. Experience in credit risk, fintech, or financial services domains. Experience working on US credit bureau data Prior experience managing or mentoring technical teams. Strong communication skills and the ability to work cross-functionally with engineers, product managers, and stakeholders. Bachelor s / master s degree in a quantitative discipline (e.g. Engineering, Computer Science, Mathematics). Scienaptic is on a mission to increase credit availability by transforming technology used in credit decisioning. Over 150 years of credit experience is embedded in Scienaptic s AI native credit decision platform. Our clients across banks, credit unions, fintech, and other lenders use the platform to constantly improve the quality of underwriting decisions. This enables them to say yes to borrowers more often and faster.
The Data Scientist role at Scienaptic will enable you to be at the forefront of latest cutting- edge technology and create a significant and visible business impact for Scienaptic. You will be working with some of the best-in-class Engineers, Data Scientists, and Business Analytics Consultants in an environment which will encourage you to contribute widely to functional and technological aspects without worrying about conventional job silos. Responsibilities Design, develop, and deploy machine learning based models for credit risk and related use cases. Present model outcomes and recommendations to internal and external stakeholders. Establish a regular cadence of client engagement including roadmap planning, updates, and reporting. Establish model monitoring, back-testing, and performance tracking frameworks. Work closely with internal teams including Client Engagement, Engineering and Product to ensure smooth integration and deployment. Skills & Competencies 4+ years of experience in data science and machine learning with prior experience in credit risk model development. Strong proficiency in Python for data analysis and model development. Sound knowledge of supervised and unsupervised machine learning techniques. Strong communication and presentation skills - ability to explain complex models to stakeholders. Experience managing client relationships or working in a consulting environment Bachelor/master s degree in a quantitative discipline (e.g., Statistics, Economics,