Sr. Data Science Engineer

hace 1 mes

San José, Costa Rica Cornerstone Building Brands A tiempo completo

About Us

Cornerstone Building Brands is a premier exterior building solutions provider serving both the residential and commercial markets across North America. The building products we manufacture are the cornerstone of the communities where people live, work and play -from homes to hospitals, grade schools to grocery stores, manufacturing facilities to municipal buildings and beyond.

Through the core values and consistent behaviors and mindsets embraced by our employees, we have built a culture dedicated to understanding our customers' needs and what matters most to their success. We know that it's our people that make the difference and we are deeply committed to building a workplace and global community where inclusion is not only valued, but prioritized, providing an environment of mutual respect where equal employment opportunities are available to all applicants and team members.

Job description

•Lead complex data analysis, feature engineering, and model development initiatives to address critical business challenges.

•Advanced statistical and machine learning techniques to derive insights and inform strategic decisions.

•Innovate and refine predictive models and machine learning algorithms, ensuring they align with business objectives and deliver measurable value.

•Champion the adoption of state-of-the-art data science and machine learning research, applying new findings to improve existing systems and methodologies.

•Guide and mentor, fostering a culture of technical excellence, continuous learning, and innovation.

•Drive the strategic planning and execution of data science projects, ensuring resource optimization and alignment with organizational goals.

•Design and oversee the implementation of robust data infrastructure, including ingestion, processing, analytics pipelines, and data warehousing solutions to enhance scalability and efficiency.

•Architect advanced solutions for automated data processing, model deployment, and continuous integration to streamline data science operations.

•Enforce strict data security and compliance standards, ensuring adherence to data privacy laws and ethical data usage.

Qualifications

•Expertise in advanced data science, machine learning, and artificial intelligence techniques, supported by a strong track record in programming languages such as Python, R, SQL, and proven software engineering methodologies.

•Proficiency in a wide array of machine learning frameworks and libraries such as TensorFlow, PyTorch, Keras, Scikit-learn, and XGBoost to build, train, and deploy models effectively.

•Deep familiarity with cloud computing platforms like AWS, Azure, and GCP, and their respective data science ecosystems (, AWS SageMaker, Azure Machine Learning, GCP AI Platform).

•Experience with containerization and orchestration technologies, including Docker and Kubernetes, to create scalable and robust data science applications.

•Knowledge of advanced analytics tools such as Apache Spark, Databricks, and H2O for handling big data sets and performing distributed computing.

•Demonstrated leadership in analytical roles, with the ability to tackle complex, ambiguous data-related challenges and drive strategic business outcomes.

•Seasoned in leading and growing data science teams, mentoring staff, and facilitating a collaborative environment for knowledge sharing and problem-solving.

•Robust project and program management expertise, capable of orchestrating multiple data initiatives, managing large-scale resources, and adhering to stringent deadlines.

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