Lead Data Scientist

📋 Description

• Spearhead the design, development, and implementation of sophisticated analytical models and AI/ML initiatives to address complex business challenges.

• Convert vague business issues into structured analytical frameworks and solution strategies.

• Supervise the complete execution of various data science projects, from defining problems to deployment and monitoring.

• Direct and assess modeling, experimentation, and implementation choices.

• Guide the selection and application of suitable data science methodologies, architectures, and tools.

• Collaborate with data engineers, AI/ML engineers, and architects to create scalable and production-ready solutions.

• Assess and propose innovative technologies, including Generative AI, with an emphasis on their business impact.

• Ensure compliance with data science standards, model validation protocols, and data governance policies.

• Provide technical leadership and mentorship to data scientists; review and guide their work across various projects.

• Convey insights, risks, and recommendations to senior stakeholders to influence decision-making.

• Contribute to the development of best practices, frameworks, and processes within the data science domain.

• Support the secure and compliant deployment of data science and AI/ML solutions.

• Ensure that solutions adhere to standards for scalability, security, and maintainability.

• Articulate complex analytical concepts and insights to senior leadership.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Operations Research, or a related quantitative discipline.

• Over 8 years of professional experience in applying data science and machine learning within enterprise settings.

• Proven track record of leading the complete delivery of AI/ML solutions in production environments.

• Strong proficiency in machine learning, advanced analytics, and cutting-edge technologies like Generative AI.

• Expertise in Python, R, SQL, and contemporary data science toolsets.

• Experience with cloud-based data platforms and scalable data architectures.

• Excellent leadership, mentoring, and cross-functional collaboration abilities.

• Capability to influence technical decisions and guide project trajectories.

• Familiarity with agile, iterative development methodologies.

• Established ability to mentor and cultivate data science talent.

• Strong skills in stakeholder engagement and leadership communication.

🏝️ Benefits

• Flexible work environment.

• Internal mobility celebration.

• Volunteering opportunities.

• Remote and hybrid positions available with necessary internet connectivity.