Director, Data Science (REMOTE: US)

Veeam®, the #1 global market leader in data protection and ransomware recovery, is on a mission to empower every organization to not just bounce back from a data outage or loss but bounce forward.

With Veeam, organizations achieve radical resilience through data security, data recovery, and data freedom for their hybrid cloud. 

The Veeam Data Platform delivers a single solution for cloud, virtual, physical, SaaS, and Kubernetes environments that gives IT and security leaders peace of mind that their apps 
and data are protected and always available.

Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 450,000 customers worldwide, including 74% of the Global 2000, who trust Veeam to keep their businesses running.

The Director of Data Science role is responsible for leading the development of data science models and AI innovations that help Veeam make informed, predictive data-driven decisions. This senior role involves overseeing a team of data scientists and collaborating with various cross-functional groups to create sophisticated predictive analytical models and AI-based solutions. Additionally, the Director of Data Science will have a direct impact by using cutting-edge data science and AI capabilities to drive business growth and enhance organizational strategies. A key part of the role will be driving AI-based innovation and leading AI projects to ensure the company remains at the forefront of technological advancements.

The ideal candidate will bridge technical and business teams, fostering collaboration to boost productivity and efficiency. By working closely with stakeholders, they will derive valuable insights from complex data, drive innovative solutions, and ensure data security and scalability. The candidate will also spearhead AI initiatives, leveraging cutting-edge technologies to develop and implement AI-driven solutions that enhance customer experience and optimize operations.

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

Key Success Factors:

• Ability to leverage data opportunities through cross-functional collaboration using AI-powered techniques
• Expertise in deploying secure, scalable data science solutions with Python, R, SQL, and AI frameworks
• Proficiency in implementing and monitoring automated anomaly detection systems using machine learning
• Aptitude in designing experiments to validate models, ensuring robust and reliable outcomes
• Innovative mindset to explore and integrate new AI technologies and methodologies
• Capability to optimize operational workflows with advanced AI and machine learning techniques
• Skill in developing and refining complex algorithms to solve unstructured problems
• Commitment to ensuring robust data quality and integrity through AI-driven cleaning and validation procedures
• Effective communication of complex analytical concepts to stakeholders
• Proven experience in leading complex data science projects from conception to implementation
• Ability to drive data-driven decision-making through innovative visualizations and predictive models
• Positive and proactive attitude when tackling challenging data sci