Job Title - Decision Science Practitioner Consultant S&C; GN

Management Level: Consultant

Location: Bangalore/ Kolkata/Gurugram/Hyderabad

Must have skills: Data Modelling, Conceptual & Logical Design, Semantic Modelling and Understanding of Knowledge Graphs

Good to have skills: Data Science, Ontologies, AI/ML Data Enablement, GenAI Foundations

Job Summary:

We are seeking a highly skilled and motivated Consultant Data Modeler to design, develop, and support the maintenance of conceptual, logical, physical, and semantic data models that support advanced analytics, AI/ML, and Generative AI use cases. The consultant will work closely with domain experts/business stakeholders, data science/engineering teams to translate complex business and system knowledge into scalable, high-quality data and semantic models. These models will serve as foundational assets enabling analytics, decision science, AI-driven insights, and intelligent automation across enterprise platforms. The role requires strong collaboration skills and the ability to work across multiple client environments.

Key Responsibilities

Project and Team Leadership

- Collaborate with business stakeholders and domain experts to understand data requirements and translate them into transparent conceptual, logical, and physical data models.
- Work closely with data engineers, analytics teams, and AI/ML practitioners to ensure data models are aligned with downstream consumption needs.
- Aptitude to work independently on modeling workstreams within client engagements, including requirements gathering, design, and documentation.
- Document & communicate modeling decisions, trade-offs, and best practices to both technical and non-technical audiences.
- Contribute to project delivery through high-quality, low-defect delivery”, documentation, design reviews,



and model governance activities.

Data Modelling & Semantic Modelling Expertise

- Design and maintain conceptual, logical, and physical data models for structured and semi-structured data across enterprise systems.
- Develop reusable, extensible data models supporting analytics, reporting, AI/ML feature engineering, and decision science use cases.
- Apply semantic modeling techniques, including domain modeling, entity relationships, hierarchies, and taxonomies.
- Enable ontology and knowledge graph modeling, translating subject-matter knowledge into machine-readable representations.
- Ensure alignment of data models with enterprise architecture principles, data standards, and best practices.

AI & GenAI Enablement

- Design data and semantic models that act as foundational datasets for AI/ML and Generative AI systems.
- Enable explainability, reasoning, and contextual grounding through ontology-driven approaches and graph-based data models.
- Partner with data science and AI teams to ensure models support feature reuse, RAG pipelines, and intelligent agent workflows.
- Contribute to data model designs that improve trust, interpretability, and scalability of AI-driven solutions.

Data Governance & Standards

- Follow and contribute to data modeling standards, naming conventions, and design guidelines across projects.
- Support data governance initiatives including metadata management, lineage, and documentation.




- Ensure consistency, quality, and reusability of data assets across platforms and use cases.

Business Impact and Innovation

- Translate complex business concepts into clear, well-structured data models that accelerate analytics and AI adoption.
- Enable faster solution development by providing high-quality, well-documented data foundations.
- Support measurable outcomes by improving data usability, consistency, and decision-making effectiveness.

Required Qualifications

Experience

- 4–6 years of experience with 3+ years of hands-on experience in data modelling, information modelling, or data architecture roles.
- Experience designing conceptual, logical, and physical data models.
- Experience working in consulting or client-facing roles is highly preferred.

Education

- Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related field.

Technical Skills

- Strong expertise in data modeling techniques and methodologies.
- Proficiency with data modeling tools (ER modeling tools, UML, or equivalent) is preferred.
- Experience working with relational and graph-based data models.
- Familiarity with semantic modeling concepts, ontologies, or knowledge graphs (e.g., RDF/OWL concepts).
- Ability to collaborate effectively with data engineers, data scientists, and business stakeholders.

Preferred Skills

- Exposure to knowledge graph technologies (e.g., Neo4j or similar).
- Familiarity with AI/ML and GenAI consumption patterns, including feature stores, RAG pipelines, and agentic systems.
- Experience defining data standards and governance frameworks.
- Prior experience supporting analytics, decision science, or AI-driven initiatives.

📌 S&C Global Network - AI - CMT - Telecom Analyst (India)
🏢 Accenture
📍 India