Director, Data Science (REMOTE: US)

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Requirements:

• Extensive experience in Data Analytics, Business Intelligence, and Reporting, with a strong focus on statistical methods
• Advanced expertise in AI and Machine Learning, including model development, deployment, and designing AI-driven solutions for business processes
• Proficient in technologies like Python, R, and TensorFlow, with formal training in Data Science and hands-on experience in machine learning libraries and data visualization techniques
• Expertise in SQL queries, Excel, PowerPoint, and SaaS systems like Salesforce
• Strong analytical skills and experience in AI-driven solutions
• Experience with cloud computing platforms such as AWS, Azure, and Google Cloud
• Proven ability to lead AI projects and implement innovative technologies that drive business value
• Strong problem-solving skills and ability to handle complex datasets to extract actionable insights
• Effective communication skills to articulate complex analytical concepts to technical and non-technical stakeholders

Responsibilities:

• Lead and mentor a team of data scientists in developing advanced machine learning models, dashboards, and visualizations for predictive analytics and decision-making
• Conduct and supervise statistical analyses and experiment-driven predictive modeling to extract actionable business insights, leveraging cutting-edge machine learning algorithms
• Present analytical findings and recommendations to stakeholders and leadership, utilizing AI for enhanced data interpretation and driving strategic decisions
• Identify and leverage data opportunities with cross-functional teams through AI-powered data mining techniques and unstructured problem-solving
• Lead the deployment of secure, scalable data science solutions using Python, R, SQL, and AI frameworks to address complex business challenges
• Implement and monitor automated anomaly detection systems using machine learning to swiftly identify and address issues
• Design comprehensive experiments to validate models, ensuring robust and reliable outcomes
• Drive innovation by continuously exploring and integrating new AI technologies and methodologies
• Optimize operational workflows using AI and machine learning techniques, enhancing efficiency and productivity
• Develop and refine complex algorithms to solve unstructured problems, applying deep learning and other advanced techniques
• Ensure robust data quality and integrity with AI-driven cleaning and validation procedures
• Communicate complex analytical concepts in a clear and concise manner to stakeholders, fostering understanding and collaboration across teams