National Healthcare Group Hiring! Full Time Assistant Manager, Data Analytics in - Ricebowl

Institution: National Healthcare Group

Family Group: Administration

Job Title

Assistant Manager, Data Analytics

Position Overview

This role supports advanced people analytics and AI-enabled HR transformation through comprehensive data analysis, AI solution development, and strategic workforce insights. The incumbent will conduct complex statistical analyses, develop machine learning predictive models, prototype AI applications, and deliver evidence-based recommendations to influence HR decision-making. With a specialised focus on compensation and benefits (C&B) analytics, the role involves end-to-end analysis of compensation structures across staff segments and institutions, market benchmarking against external data, designing increment and bonus matrices, and conducting productivity-linked payment analysis. The position requires creating interactive dashboards and translating analytical findings into actionable insights that support HR operations, strategic planning, and compensation strategy optimisation.

Key Responsibilities

• Advanced Analytics

– Conduct statistical and machine learning analyses to inform talent strategies and workforce planning.

– Perform comprehensive compensation and benefits analysis across staff segments, family groups, and institutions within NHG, including market benchmarking to identify competitive positioning and gaps.

– Analyse compensation positions against external benchmarks and design annual increment and bonus matrices.

– Generate earnings analysis and cost analysis across various compensation components.

– Compute statistical norms on workload and doctors' productivity metrics, and create performance-linked payment plans and matrices.

– Translate analytical findings into clear, actionable recommendations for HR and institutional leaders.

• Generative AI & Product Development

– Drive and support the lifecycle of GenAI solutions for HR use cases—from ideation and prototyping to user testing and deployment.

– Assess emerging AI technologies and translate them into practical, scalable HR applications.

– Support proof-of-concept studies to evaluate new AI/ML methods and tools.

– Collaborate with cross-functional HR and technical teams to ensure solutions meet business needs.

– Lead knowledge-sharing initiatives and actively contribute expertise to learning activities across the HR community.

• Dashboarding, Reporting & Automation

– Combine and clean raw data from various sources, mapping into structured databases ready for analytical use.

– Create comprehensive reports by combining data from multiple systems.

– Implement automation solutions to streamline reporting.

– Develop interactive dashboards and self‑service analytics tools for senior HR leaders and institutional leadership.

Required Qualifications

Education & Experience

• Bachelor's degree in Data Science, Statistics, Computer Science, Business Analytics, Applied Mathematics or related fields.

• Experience or internship in machine learning and AI preferred.

Technical Skills

• Strong foundation in statistical analysis, machine learning, and predictive modelling.

• Proficiency in Python, experienced with libraries such as pandas, NumPy, scikit‑learn.

• Hands‑on experience with GenAI tools and LLM workflows, including RAG, prompt engineering, and model deployment.

• Skilled in dashboarding tools (e.g., Tableau), with working knowledge of cloud platforms (AWS preferred).

• Familiarity with RPA tools (e.g., UiPath) is an advantage.

Soft Skills & Attributes

• Strong analytical and problem-solving abilities with attention to detail and accuracy in handling sensitive compensation data.

• Excellent communication skills with ability to translate complex insights to non-technical audiences and create highly compelling, professional PowerPoint presentation decks for senior leadership.

• Growth mindset and adaptability to evolving AI technologies.

• Collaborative, proactive, and confident working with cross-functional stakeholders.