Data Scientist (Microsoft 365 Copilot / AI)

What matters most

• Build Copilot agents for engineering work

  Design and configure agents in Copilot Studio, alongside custom applications and utilities that address engineering and business requirements. The posting also names Agentic Framework, Azure AI Studio, and Azure OpenAI Service as mandatory skills.

• Ground outputs in project knowledge

  Connect agents to SharePoint and Microsoft 365 project data for secure, accurate retrieval. Prompts, topics, workflows, and guardrails should support consistent, reference-based answers.

• Deliver document and workflow solutions

  Develop intelligent search, document processing, OCR, retrieval-based solutions, and workflow automation, integrating enterprise data and APIs where needed.

• Validate needs and support adoption

  Work with engineering and digital teams to validate requirements, deliver solutions, and support use across engineering, EPC, and project workflows.

Likely challenges to think through

• Balancing retrieval usefulness with access control

  A likely design challenge is making past project knowledge easy to find without exposing information a user should not see or presenting unsupported answers. Prepare to explain how you would respect source permissions and test answers against their references.

• Handling uneven document quality

  OCR and retrieval may have to accommodate documents whose extracted text is incomplete or difficult to search; that is a preparation hypothesis, not a stated condition of the employer's data. Prepare an approach for checking extraction quality and deciding when an agent should flag uncertainty rather than answer.

• Choosing the right level of automation

  Engineering workflows may benefit from automation while still needing human review for consequential outputs. Prepare to describe how you would validate requirements with users, define where review belongs, and assess whether a solution is useful before wider adoption.

Topics to prepare

• Agentic Framework and orchestration

  Mandatory skill. Sketch how an agent decides when to retrieve project information, call an API, or stop and ask for clarification. Explain how each decision supports the posting’s AI-agent and automation work.

• Azure AI Studio and Azure OpenAI Service

  Both are mandatory skills. Review their roles in building and testing an AI-enabled enterprise solution; draw a simple architecture connecting them to a Copilot agent and enterprise data. The architecture is a preparation exercise, not a prescribed employer design.

• Secure Microsoft 365 and SharePoint grounding

  The role calls for secure, accurate retrieval from project data. Walk through a hypothetical question answered from two SharePoint documents, identifying which references support the answer and when the agent should decline to answer.

• Retrieval and document understanding

  The posting names intelligent search, document processing, OCR, and retrieval-based systems. Compare how a scanned drawing and a text document would enter a search workflow, then identify likely extraction and retrieval errors to check.

• Engineering and EPC project context

  The role applies AI tools to engineering and project workflows; relevant domain experience is preferred. As a preparation suggestion, map a past-project-knowledge question to the documents, stakeholders, and validation needed before its answer could be reused.

Skills to revise

• Configure a Copilot Studio agent

  The posting explicitly asks for Copilot Studio agents. Practise configuring a small agent with a project-information topic and a workflow, then test a question it can answer and one it should escalate or leave unanswered.

• Write reference-based prompts and guardrails

  The role calls for prompts, topics, workflows, and guardrails. Draft instructions requiring cited project references, then test them against an ambiguous question and a question unsupported by the available documents.

• Prototype an Azure-backed agent interaction

  For the mandatory Azure AI Studio and Azure OpenAI Service skills, rehearse a small test interaction and explain how you would inspect its output for accuracy and consistency. This is a suggested exercise, not a specified project.

• Test a document-to-answer workflow

  The posting calls for OCR, intelligent search, and document processing. Using sample project documents, practise extracting text, finding relevant passages, and checking whether the resulting answer matches its references.

• Integrate an application, data, and an API

  Custom applications, APIs, enterprise data, and automation are explicit requirements; the skills list also names ASP.NET, Visual Studio, SQL Server, Oracle, VBA, Python, and Java. Rehearse explaining one small integration in a listed language or application environment, including its data query and error handling, without assuming a particular stack for the employer.

• Validate requirements with stakeholders

  The role involves engineering and digital teams and supporting adoption. Practise turning a hypothetical project-search request into a short acceptance checklist covering the intended users, permitted sources, answer quality, and a review with both technical and business stakeholders.

• Map evidence to the required skills

  Prepare a one-page matrix of work you can discuss for the posting’s mandatory Agentic Framework, Azure AI Studio, and Azure OpenAI Service skills, plus Copilot Studio and enterprise data. Note your specific contribution and outcome for each example; leave gaps explicit.

• Prepare an agent project walkthrough

  Select a real project, if available, and explain the requirement, your agent design, prompts or topics, workflow, guardrails, testing, and outcome. The role specifically calls for Copilot Studio agents grounded in SharePoint and Microsoft 365 project data; do not present a hypothetical exercise as delivered work.

• Sketch a secure knowledge-retrieval design

  As interview practice, draw a hypothetical agent that helps an engineering team reuse past project documents. Show how it would retrieve permitted SharePoint content, provide references, handle missing evidence, and be checked for accuracy. This is a suggested exercise, not a stated employer assignment.

• Work through a document-automation scenario

  Prepare a short design for extracting information from scanned project documents using OCR, document processing, intelligent search, and a review step. Explain where an API or workflow automation would fit and how you would check extraction errors.

• Organize application and integration examples

  Have concise examples ready for the listed application, database, scripting, and API skills: ASP.NET and Visual Studio; SQL Server and Oracle; VBA, Python, and Java. For each example you actually have, identify the data flow, your implementation decisions, and the result.

• Prepare a collaboration and adoption example

  Outline a real instance, if available, of validating requirements with technical and business stakeholders, adjusting a solution from feedback, and supporting its use. Connect it to the posting’s engineering, EPC, and project-workflow context without implying experience you do not have.

• Draft targeted employer questions

  Ask which engineering workflows and data sources are the initial priorities, how access to project knowledge is controlled, and how agent outputs and adoption will be evaluated. Clarify the posting’s 'Pan India' location wording alongside its Vadodara job location and work-from-office designation.