Senior Manager, Data Science

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and manage scalable ETL/ELT processes that support enterprise reporting, advanced analytics, machine learning, and AI initiatives.

• Collaborate with IT, HRIS, and business units to enhance data accessibility, reliability, quality, and governance.

• Set standards and best practices for data ingestion, transformation, integration, and quality assurance.

• Actively participate in the development and optimization of data pipelines, data models, and analytical datasets.

• Ensure that analytical solutions utilize reliable, governed, and well-structured data assets.

• Create executive-level reports on data science outcomes, model performance, and organizational impact.

• Define success metrics and track the business benefits resulting from analytics initiatives.

• Guarantee that projects are delivered on time, within scope, and yield measurable returns.

• Provide guidance to senior leadership on analytics, AI, and emerging technologies.

• Promote the adoption of analytical solutions and measure their business impact.

• Develop and implement the Operations data science roadmap in alignment with company objectives.

• Convert business challenges into data-driven strategies and solutions in collaboration with executive and operational leaders.

• Identify and prioritize opportunities for predictive analytics, machine learning, optimization, and AI applications.

• Lead and mentor Data Scientists, Senior Analysts, and Analysts.

• Offer strategic direction while engaging in hands-on technical execution and leadership.

• Build organizational data science capabilities through coaching, technical development, and succession planning.

⛳️ Requirements

• Over 10 years of experience in a data science or advanced analytics role.

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative discipline.

• At least 3 years of experience managing direct reports.

• Proven success in delivering business value through predictive analytics, machine learning, optimization, or AI initiatives.

• Experience in applying statistical modeling and machine learning techniques to practical business challenges.

• Background in leading cross-functional projects.

• Demonstrated leadership and influencing capabilities.

• Experience across the complete analytics lifecycle, from data acquisition and transformation to insight generation and operationalization.

• Proven experience in deploying advanced analytics, predictive modeling, optimization, and AI-driven solutions in production environments.

• Proficiency in designing and maintaining ETL/ELT pipelines and data integration processes.

• Familiarity with consuming and integrating APIs for data capture and ingestion.

• Ability to translate business requirements into technical and data specifications.

• Advanced proficiency in Python, SQL, and contemporary data transformation frameworks.

• Experience with cloud-based analytics environments and modern data platforms.

• Strong understanding of data modeling, data warehousing, and analytics engineering principles.

• Experience with GIT for configuration control.

• Excellent interpersonal, communication, and collaboration skills.

• Leadership presence with the ability to engage effectively with executive leaders and frontline team members.

• Willingness and capability to lead through strategic direction and hands-on technical execution.

• Ability to perform under competing priorities.

• Willingness to travel up to 20% of the time.

• Ability to convey complex analytical concepts and model results to non-technical stakeholders.

• Strong business acumen linking analytical outcomes to operational and financial performance.

🏝️ Benefits

• Medical/prescription drug, dental, and vision insurance.

• Health Savings Account.

• Flexible Spending Accounts.

• Life insurance.

• Disability insurance.

• 401(k).

• Critical illness, hospital indemnity, and accident insurance.

• Identity theft and legal services.

• Paid time off.

• Paid maternity leave.

• Tuition reimbursement.

• Training and development opportunities.

• Employee Assistance Program (EAP) & perks.

• Volunteer and community-giving initiatives.

• Professional development resources.