Data Scientist

Cornerstone Building Brands is hiring for one Data Scientist for an 18-month contract role. The candidate must be located within Eastern Standard Time Zone in the US.

Job Summary:  
•    Lead complex data analysis, feature engineering, and model development initiatives to address critical business challenges. Utilize 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 a team of data science professionals, fostering a culture of technical excellence, continuous learning, and innovation. 
•    Drive the strategic planning and execution of data science projects, ensuring resource optimization, timely delivery, 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. 
•    Developed business acumen to provide insights and direction to business leaders.  

Job 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 (e.g., 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.