Enterprise Sales Engineer

Roles and responsibilities

Team Management

• Develop and lead the Enterprise Analytics & Intelligence team by implementing team objectives and goals aligned with corporate strategy and corrective action plans if needed.
• Manage team members' development plans per their aspirations/capabilities and corporate needs.

Market & Customer Intelligence

• Build a market and customer intelligence framework to monitor major global, regional, and local customer behavior trends.
• Structure data, develop a deep understanding of market trends and customer usage patterns, and translate it into business insight to be shared to support digital health services/assets/ecosystem development and marketing initiatives.

Strategic Planning, Solutions Innovation & Performance Monitoring

• Develop and implement an Enterprise Analytics & Intelligence strategy at the corporate and service level aligned with company business objectives to achieve strategic goals focusing on profitable growth and client retention.
• Identify and implement new solutions to enhance the deliverables of the function.
• Investigate market demand, generate and contribute to innovation proposals that include market analysis, business justification, target customers and projected revenue, engaging, if needed, local markets
• Manage and report on all services and set benchmarks and measures for key performance indicators of success. Report on effectiveness and adjust strategy as necessary to maximize results.
• Communicate and align plans and roadmaps with critical stakeholders, including IT Solutions teams, and hold them accountable for maintaining the best customer experience and achieving business Impact.

Go to Market

• Support business managers to analyze the market and customer base and identify new opportunities for existing products in the most consistent and standardized approach
• Work closely with the PM&I and Digital Services teams to develop client and customer reporting and analysis for key market stakeholders, B-partners, and end customers

What you bring

• Education: Master’s Degree in related fields
• Experience: A minimum of 6 years’ experience in Data Science, Predictive modelling, Insurance, TPA, Banking, or large E-comms.
• Physically fit to carry out duties
• Legally permitted to work in the country of operations.
• Extensive hands-on experience in building and executing complex analytical and statistical projects and analyses using advanced statistical modelling techniques in a business setting
• Experience in health insurance-specific/TPA predictive analytics is a strong plus

Desired candidate profile

• Strategic Leadership and Vision:

  • Develop Analytics Strategy: Define the vision, strategy, and roadmap for analytics and business intelligence across the organization. Ensure alignment with corporate goals and objectives.
  • Leadership of Analytics Function: Lead, inspire, and manage the analytics and business intelligence teams, fostering a data-driven culture within the organization.
  • Executive Collaboration: Collaborate with senior leadership, including the C-suite, to integrate analytics and intelligence into business decision-making and strategic initiatives.
  • Data Governance and Compliance: Ensure that analytics and data usage comply with industry regulations, privacy standards, and internal policies (e.g., GDPR, CCPA).

• Data Strategy and Architecture:

  • Data Integration: Oversee the integration of disparate data sources (internal and external) to create a unified data platform that provides comprehensive and accurate insights.
  • Data Quality Management: Implement data governance practices to ensure that data is accurate, clean, consistent, and reliable for business decision-making.
  • Data Infrastructure Oversight: Oversee the design and management of the organization's data architecture, ensuring that the infrastructure supports both current and future analytics needs.
  • Big Data and Cloud Strategy: Manage large-scale data initiatives, including the implementation of big data technologies and cloud platforms (e.g., AWS, Azure, Google Cloud) to scale the analytics function.

• Analytics and Business Intelligence (BI) Execution:

  • Advanced Analytics: Lead the implementation of advanced analytics solutions, including predictive analytics, machine learning, AI (artificial intelligence), and prescriptive analytics to uncover trends, optimize processes, and provide actionable insights.
  • Business Intelligence Tools: Oversee the use of BI tools (e.g., Tableau, Power BI, Qlik, Looker) for reporting, data visualization, and decision support.
  • KPI and Metric Development: Define key performance indicators (KPIs) and metrics for various business functions and departments to monitor progress and performance.
  • Insight Delivery: Ensure that actionable insights are delivered in a timely manner to key stakeholders across the organization, enabling data-driven decision-making.

• Team Management and Development:

  • Build and Lead Teams: Lead a high-performing team of data scientists, data engineers, business analysts, and BI professionals, guiding them to achieve business objectives.
  • Talent Development: Foster a culture of continuous learning by supporting the professional development of team members and ensuring they stay ahead of industry trends.
  • Cross-Functional Collaboration: Collaborate closely with other departments (e.g., Marketing, Sales, Finance, Operations, IT) to understand their data needs and provide actionable insights that align with their goals.

• Business Insights and Decision Support:

  • C-Suite Reporting: Provide senior executives with data-driven insights and actionable recommendations that support strategic decisions, investment choices, and business growth.
  • Market Intelligence: Oversee the collection and analysis of external market data to identify opportunities, trends, and competitive intelligence to inform business strategy.
  • Customer Analytics: Lead initiatives to analyze customer data (e.g., behavior, segmentation, lifetime value) to drive marketing, sales, and product decisions that enhance customer acquisition and retention.