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NewFull-time· ai · ml
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Accenture

Data Science Associate

Pay

₹5L–8L LPA

+22% vs avg

Location

Bangalore, Kolkata, Gurugram

On-site

Batch

2024, 2025, 2026

eligible

Closes

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Posted 2h ago · 3,591 views this week

₹5L–8L LPA

Full-time · Bangalore, Kolkata, Gurugram · On-site

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Description

About the role

The Data Science Associate (Decision Science Practitioner Associate) role at Accenture focuses on building and testing Generative AI‑powered applications, retrieval‑augmented generation (RAG) solutions, and conversational AI agents. Candidates will work on Python‑based development, API integration, and cloud AI services while collaborating with senior practitioners.

Responsibilities

  • Develop LLM‑driven applications using prompts, APIs and established Generative AI frameworks.
  • Prepare, organise and validate knowledge sources for RAG pipelines.
  • Assist in building and testing conversational AI agents and workflows.
  • Perform functional testing and validation of AI outputs against defined test cases.
  • Analyse response quality, identify improvement areas and document findings.
  • Support Azure and/or AWS AI service configuration, testing and monitoring.
  • Apply enterprise security and access‑management standards.
  • Write Python components and integrate them with APIs and enterprise systems.
  • Use Git and standard development practices for source‑code management.
  • Prepare documentation and aid in testing, troubleshooting and deployment activities.

Eligibility

  • Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Statistics, Applied Mathematics, Engineering or a related quantitative discipline.
  • 0–2 years of hands‑on experience in AI/ML, data science, software engineering or analytics.

Skills

  • Python programming
  • SQL querying
  • Generative AI fundamentals
  • Prompt engineering
  • REST API integration

Benefits

    Skills

    · 10 total

    Required5

    pythonsqlgenerative aiprompt engineeringapis

    Nice to have5

    ragagentic ailangchainlanggraphmachine learning