Req ID: 188045

General Purpose

This role holds a leadership position and manages the work of Data Scientists who design and develop advanced analytics models. They provide technical guidance and manage the day-to-day development and validation tasks for the team, ensuing the quality of the solutions.

Duties and Responsibilities

• Manages the day-to-day tasks and development work of Data Science resources to ensure alignment with objectives and deliverables
• Provides technical guidance and validation of the Data Science development work to ensure model quality and accuracy
• Oversees the creation of quality metrics for the implementation and execution of Advanced Analytics projects, reporting them to key stakeholders
• Leads the design of experiments and testing to be followed during the pilot phase in the AA projects
• Ensure the scalability, stability, and performance of the code and models developed by the DS team.
• Ensure technical alignment with the Data Science team from HQ.

• Bachelor's degrees in Computer Science, Statistics, Mathematics or related field.
• Advanced degree, Masters or PhD, is a plus.
• 3+ years of experience in data science, including hands-on experience in data analysis and model design, development, and execution
• 3+ years proven experience leading and managing a team of data scientists, including setting goals, providing guidance, assigning tasks, and evaluating performance.
• Expert in data analysis, machine learning, statistical modeling, and data manipulation.
• Proficient in tools and languages like Python, R, SQL, and machine learning libraries/frameworks.
• Strong grasp of the organization's goals, industry, and competitive landscape. They should be able to align data science efforts with business objectives.
• Strong written and verbal communication skills to convey complex technical findings to both technical and non-technical stakeholders.
• Proficiency in project management methodologies to ensure the efficient execution of data science projects, including resource allocation, timelines, and project prioritization.
• 30% travel expected