Role Description The Chief Data Scientist at SAC BRENNUS will lead the design and implementation of advanced data science solutions to support strategic decision-making and product innovation. This full-time remote role involves overseeing end-to-end data workflows, including data collection, cleaning, modeling, and deployment into production environments. The person in this role will define the data science roadmap, guide the development of predictive models and pattern recognition systems, and collaborate with cross-functional teams to translate business needs into technical requirements.
Day-to-day tasks include conducting exploratory data analysis, mentoring and managing data science team members, reviewing model performance, ensuring best practices in coding and documentation, and presenting findings to technical and non-technical stakeholders.
The Chief Data
Scientist will also stay current with emerging techniques and tools, recommend improvements to the data infrastructure, and help shape data governance and ethical AI guidelines.
Qualifications
Strong foundation in Computer Science and Data Science, including algorithms, data structures, and applied machine learning.
Expertise in Statistics and Analytical Skills to design experiments, interpret data, and validate models rigorously.
Advanced Pattern Recognition capabilities for building and optimizing models in areas such as classification, clustering, and anomaly detection.
Proficiency in programming languages commonly used in data science (e.g., Python, R) and experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Experience leading data science teams, managing projects, and collaborating with engineering, product, and business stakeholders.
Ability to communicate complex technical concepts clearly to varied audiences and to produce concise reports and presentations.
Background in designing and deploying models to production environments, including familiarity with cloud platforms and MLOps practices.
Advanced degree (Master’s or PhD) in Computer Science, Data Science, Statistics, or a related quantitative field, or equivalent practical experience.