Sr. Data Scientist

Purpose of the Job

Staff AI Engineer leads and drives advanced AI initiatives within the organization. By leveraging mastery in advanced statistical methods, machine learning, and programming, the Staff AI Engineer is responsible for designing and implementing complex AI solutions. This role involves innovatively solving business problems, optimizing algorithms, and deploying AI models to provide data-driven insights that align with the organization's strategic goals. Additionally, the Staff AI Engineer ensures efficient workflows, automates processes, and effectively communicates insights to stakeholders, aiming to enhance productivity, strategic decision-making, and overall business success.

Job Description

Responsibilities & Accountabilities

• Lead the design and development of complex AI solutions, employing advanced techniques to optimize algorithms and data sets for superior performance.
• Design and implement experiments to rigorously evaluate AI solution performance and provide valuable insights for refinement.
• Develop detailed AI solution requirements and effectively manage the development process, adapting to changing circumstances and requirements.
• Collaborate effectively with cross-functional teams and stakeholders, ensuring successful delivery while adapting to evolving needs and circumstances.
• Stay updated with the latest trends and advancements in AI technology, incorporating newfound knowledge into solution design and development.
• Apply mastery of statistical methods, machine learning algorithms, and programming languages to analyze unstructured data and derive actionable insights.
• Develop novel modeling techniques and algorithms, utilizing advanced methodologies like Bayesian inference, reinforcement learning, and causal inference.
• Create scalable models capable of handling large volumes of real-time data, ensuring transparency and explainability in the model's functioning.
• Develop models that inform strategic decision-making at the highest organizational levels, leveraging advanced machine learning techniques.
• Align business objectives with innovative data science solutions, proactively identifying opportunities for data-driven insights and product innovations.
• Develop and implement advanced AI models, utilizing techniques like transfer learning, ensemble methods, and neural networks for complex problem-solving.
• Design and implement efficient workflows, automate data-related tasks, and lead process improvement initiatives to enhance productivity and data accuracy.
• Lead product development efforts, demonstrating an understanding of the business model and leveraging data for product decision-making and roadmap planning. Ethical Product Development : Understand and consider the ethical and legal implications of data-driven products and solutions, ensuring responsible and compliant development practices.

Performance Measurement

Educational and Experience Requirements

Competencies and Behaviors

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