Lead Data Scientist

Project Lead Experience

Building Data Sets

Presenting to A-C level executives

Must have Cogito experience

AWS Certification is a MUST

Key Responsibilities

• Team Management : Lead and mentor a team of data scientists, machine learning engineers, and big data specialists to foster professional growth and collaboration.
• Project Planning : Oversee the planning and execution of data science projects, ensuring alignment with organizational goals and objectives.
• Model Development : Build and optimize analytical models using machine learning, natural language processing, and statistical techniques to derive insights from large datasets.
• Data Analysis : Analyze various data sources, including procurement, supply chain, and healthcare data, to inform business strategies and product development.
• Problem Solving : Identify and address data development challenges, proposing innovative solutions to enhance data utilization across the organization.
• Methodology Development : Lead the development and maintenance of methodologies that support product offerings, including statistical modeling and time-series analysis.
• Stakeholder Collaboration : Work closely with business leaders and other departments to communicate analytical findings and drive data-driven decision-making.

Required Skills and Qualifications

• Educational Background : Typically requires a Masters or Ph.D. in Statistics, Computer Science, Mathematics, or a related field.
• Technical Expertise : Proficiency in data manipulation, visualization, and machine learning techniques, with experience in programming languages such as Python, R, or SQL.
• Analytical Skills : Strong problem-solving abilities and a knack for statistical analysis to interpret complex data sets effectively.
• Leadership Skills : Experience in managing teams and projects, with the ability to mentor junior data scientists and foster a collaborative environment.
• Communication Skills : Excellent verbal and written communication skills to convey complex analytical concepts to non-technical stakeholders.