Associate Data Scientist, AI & Data Analytics

IBM

Confirmed live yesterday Trusted

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Work type: On-site
Location: —
Posted: 26 days ago
Freshness: Confirmed live yesterday

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How this pay compares to similar roles

Similar $156k

$86k most similar roles pay here $222k

This listing doesn't post a salary. Most similar roles pay $126,800–$185,225.

Based on 240 similar postings.

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About IBM

IBM is a US-based global technology company providing hybrid cloud, AI, consulting, enterprise software, and IT infrastructure products and services.

IBM currently has 506 open roles on FindRole.

Listed pay typically runs $174,632–$197,165 across 5 roles with salary data.

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At a glance

TL;DR · Associate Data Scientist, AI & Data Analytics

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Associate Data Scientist 2027 - AI & Data Analytics is a role within the IBM Consulting team where you will solve complex business problems using statistics, machine learning, and data science techniques. You will work in an Agile environment to prepare, cleanse, and analyze structured and unstructured data while building generative AI, RAG, and agentic AI workflows. The role involves designing experiments, evaluating model performance for accuracy and bias, and translating technical results into actionable recommendations for diverse stakeholders. To succeed, you must possess strong fundamentals in mathematics, statistics, and computer science. You will utilize tools such as Python, R, SQL, and TensorFlow, alongside frameworks like LangChain, LlamaIndex, or Semantic Kernel. The work focuses on delivering responsible AI practices to address client challenges involving digital transformation, cloud strategy, and automated intelligence systems.

What does a Data Scientist earn?

Median $162025 from 276 postings across 61 companies.

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Skills

Python R SQL TensorFlow Machine Learning Generative AI Agentic AI RAG LangChain LangGraph LlamaIndex Semantic Kernel AutoGen MLOps LLMOps CI/CD Git AWS Azure Google Cloud Vector Databases

What you'll do

Prepare, cleanse, join, and analyze structured and unstructured data for machine learning and AI workflows.
Implement and validate predictive, prescriptive, and statistical models to achieve measurable business outcomes.
Design experiments, prompts, and evaluation datasets to assess model accuracy, reliability, and potential bias.
Build and evaluate GenAI, RAG, and agentic AI workflows including retrieval quality and tool-use performance.
Translate complex technical results into clear, actionable recommendations for both technical and non-technical stakeholders.
Collaborate with cross-functional teams to identify critical data and select appropriate modeling techniques for client challenges.
Communicate directly with clients to understand business needs and explain model assumptions and limitations.

What we're looking for

High School Diploma or GED required.
Bachelor's degree in a related quantitative field (preferred).
Strong fundamentals in mathematics, statistics, computer science, algorithms, and analytical reasoning.
Familiarity with programming languages such as Python, SQL, R, or similar.
Foundational understanding of predictive modeling, machine learning, GenAI, and Agentic AI.
Basic understanding of cloud environments, data platforms, or AI platforms like AWS, Azure, or Google Cloud.
Experience in data science projects, internships, or portfolio work involving ML and GenAI (preferred).
Familiarity with LLMs, RAG, vector databases, and orchestration frameworks like LangChain or LlamaIndex (preferred).

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