Director of Data Science

Company Description AuroraFI is a data-driven financial technology organization focused on building innovative solutions that help clients make smarter decisions and manage risk more effectively. The company leverages advanced analytics, machine learning, and modern data platforms to deliver actionable insights across its products and services. Team members collaborate across technology, product, and business functions to solve complex problems in a fast-paced, results-oriented environment. AuroraFI values transparency, continuous learning, and a culture where diverse perspectives and inclusive practices drive better outcomes for customers and colleagues.
Role Description The Director of Data Science is a full-time remote role responsible for leading the data science function at AuroraFI and driving strategic use of data across the organization. This role oversees the design, implementation, and optimization of statistical models, machine learning solutions, and analytics frameworks that support product development, risk management, and operational efficiency. Day-to-day activities include managing and mentoring a team of data scientists and analysts, prioritizing projects, reviewing methodologies, and ensuring rigorous analytical standards. The Director collaborates closely with engineering, product, and business leaders to translate complex data findings into clear recommendations, define key performance metrics, and support data-informed decision-making. The role also involves establishing best practices for data governance, model validation, and experimentation, while staying current with emerging tools and techniques in data science and applied statistics.
Qualifications
Strong foundation in Statistics and Statistical Modeling, with experience designing and validating models for real-world business applications.
Advanced Data Science and Data Analytics skills, including experience with end-to-end model development, deployment, and performance monitoring.
Excellent Analytical Skills, with the ability to frame problems, interpret complex datasets, and communicate insights to technical and non-technical stakeholders.
Proficiency in programming languages commonly used in data science (e.g., Python, R, SQL) and familiarity with modern data platforms and cloud environments.
Demonstrated experience leading and mentoring data science or analytics teams, including setting strategy, establishing standards, and managing project pipelines.
Background in financial services, fintech, or a similarly data-intensive domain is beneficial, along with experience working with risk, pricing, or customer analytics.
Strong communication and collaboration skills, with the ability to influence decisions and build partnerships across cross-functional teams in a remote setting.
Advanced degree (Master’s or PhD) in a quantitative field such as Statistics, Mathematics, Computer Science, Data Science, Economics, or related discipline preferred.

Work arrangement
Yes