Chief Data Scientist

Role Description This is a full-time remote role for a Chief Data Scientist at SAC BRENNUS. The Chief Data Scientist will lead the design and implementation of data science strategies, including end-to-end development of advanced analytics, machine learning models, and decision-support tools. Daily responsibilities include defining data science roadmaps, overseeing data collection and preprocessing, conducting exploratory data analysis, and translating complex findings into clear, actionable insights for business and technical stakeholders. The role involves mentoring and guiding data science and engineering teams, establishing best practices for model development and deployment, and collaborating with leadership to identify high-impact opportunities where data can drive innovation and value. The Chief Data Scientist will also evaluate new technologies, tools, and methodologies to continuously improve SAC BRENNUS’s data capabilities and ensure models are ethical, robust, and scalable.
Qualifications
Strong foundation in Computer Science, including algorithms, data structures, and software engineering principles.
Advanced expertise in Data Science, with experience building and deploying machine learning and AI models in production environments.
Solid knowledge of Statistics and statistical modeling, including hypothesis testing, regression, and experimental design.
Demonstrated Analytical Skills and Pattern Recognition abilities to identify trends, anomalies, and opportunities in complex datasets.
Proficiency with common data science tools and languages (e.g., Python or R, SQL, libraries such as pandas, scikit-learn, TensorFlow or similar).
Experience leading data teams, setting technical direction, and collaborating with cross-functional stakeholders at senior levels.
Ability to communicate complex quantitative concepts clearly to non-technical audiences and influence strategic decisions.
Master’s or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience.
Experience with cloud-based data platforms and MLOps practices (e.g., model monitoring, versioning, and lifecycle management) is highly beneficial.
Commitment to responsible and inclusive use of data, with awareness of bias, fairness, and privacy considerations in data science solutions.

Work arrangement
Yes