Data Science Lead

Summary We are seeking an experienced Data Science Lead to drive strategic initiatives within our IT Services sector. In this pivotal role, the successful candidate will oversee the end-to-end lifecycle of advanced analytics projects, ensuring that data-driven solutions align with broader business objectives. This position demands a deep understanding of complex datasets and the ability to translate technical insights into actionable business strategies, serving as a critical bridge between technical teams and organizational stakeholders.

Responsibilities

Cultivate strong relationships with key stakeholders to define project scope, manage expectations, and ensure deliverables meet business needs. Execute advanced feature engineering and rigorous model evaluation processes to enhance predictive accuracy and model performance. Implement strategies for continuous model optimization to maximize efficiency and scalability across various data pipelines.

Establish robust production monitoring frameworks to track model health, detect drift, and ensure reliable real-time performance. Apply critical problem-solving and analytical thinking skills to address complex data challenges and uncover hidden opportunities. Design and develop sophisticated machine learning and statistical models tailored to specific industry requirements.

Utilize Python programming expertise to build, test, and deploy scalable machine learning solutions into production environments. Lead the full spectrum of model development and deployment, ensuring seamless integration with existing IT infrastructure.

Requirements

Possess 8 to 12 years of professional work experience within the technology or data science domain. Demonstrate proven expertise in stakeholder management and the ability to communicate technical concepts to non-technical audiences. Show advanced proficiency in feature engineering, model evaluation, and optimization techniques.

Have a strong track record in setting up production monitoring systems and maintaining model reliability. Exhibit exceptional problem-solving capabilities combined with deep analytical thinking skills. Hold extensive knowledge of machine learning algorithms and statistical modeling methodologies. Be highly skilled in Python programming for data manipulation, analysis, and software development.

Possess hands-on experience in the complete lifecycle of model development and deployment in live environments.