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Data Science Principal

💼 Full-time🗓 2026-07-28

Core

Lead data-driven initiatives for large financial institutions by designing, developing, and deploying cutting-edge machine learning models.

Role type

Principal Data Scientist (Technical Lead)

Builds

Production ML models and data science solutions for financial institutions

Domain

Finance / Machine Learning

Deliverable

production ML models

Required skills

Python, classification and regression techniques, deep learning, FastAPI, Django REST, Docker, Linux, end-to-end model lifecycle management, feature engineering, model validation

Preferred skills

Cloud platform experience (Azure, GCP, AWS), mentoring junior data scientists

Technologies

Python, FastAPI, Django REST, Docker, Azure, GCP, AWS

Responsibilities

Design and deploy explainable machine learning models; oversee the entire model lifecycle from EDA to monitoring; mentor junior data scientists; collaborate with data engineering and product teams to integrate solutions into production

Seniority

Principal, hands-on IC with leadership responsibilities

Rewrite
## About the role We are seeking an experienced Data Science Principal to lead and drive some of our data-driven initiatives for some of the largest financial institutions in the region. The ideal candidate will have a strong foundation in data science, with hands-on experience across the entire modelling lifecycle. You will be responsible for designing, developing, and deploying cutting-edge machine learning models and solutions that deliver real business impact. ## Responsibilities - Data Science Expertise: Apply a deep understanding of both conventional machine learning and deep learning techniques to develop robust explainable models that meet business requirements. - End-to-End Model Lifecycle Management: Oversee and actively participate in every phase of the data science process, including requirements gathering, exploratory data analysis (EDA), target variable selection, feature engineering, model building, model selection, validation, deployment, documentation, and ongoing monitoring. - Cloud-Native Development: Leverage your extensive experience with cloud platforms (Azure, GCP, or AWS) to design scalable and efficient data science solutions. - Technical Leadership: Mentor and guide junior data scientists, providing technical direction and support to ensure high-quality output and adherence to best practices. - Collaboration: Work closely with cross-functional teams, including data engineering, product management, and software development, to integrate data science solutions into production systems. ## Requirements - Experience: Minimum of 4 years in data science, with at least 2 years in an individual contributor role. - Technical Skills: Proficiency in Python, with strong expertise in classification and regression techniques, deep learning, and deployment frameworks such as FastAPI or Django REST. - Deployment and Operations: Experience with containerization technologies like Docker and familiarity with Linux environments. - Problem-Solving: Strong analytical and problem-solving skills, with the ability to translate complex business problems into data science solutions. ## What we offer - Innovative Environment: Be part of a dynamic team that values creativity and encourages the exploration of new ideas. - Growth Opportunities: Engage in continuous learning and professional development opportunities to stay at the forefront of data science advancements. - Impactful Work: Contribute to projects that make a tangible difference to our business and customers. ## About the company If you're passionate about data science and ready to take on a leadership role in a forward-thinking company, we'd love to hear from you.
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