Associate Data Scientist - Entry Level; Baton Rouge, LA

Position: Associate Data Scientist - Entry Level (Baton Rouge, LA)

Associate Data Scientist – Entry Level (Baton Rouge, LA)

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Introduction

You will join IBM Consulting via our world class Associate Program for university hires. As an Associate at IBM Consulting you will have the opportunity to work with a diverse range of clients worldwide. Our clients' technical and business needs are constantly evolving. We're hiring inspired, talented individuals, who believe no problem is too big to solve. We focus on your professional development through ongoing learning, mentorship, development of technical skills, and continuous personal growth, all grounded in a culture of coaching and career advancement.

If you see yourself as someone who never stops learning and who wants to unleash your potential, the IBM Consulting Associates Program is for you.

Your Role And Responsibilities

As an Associate Data Scientist at IBM, you will work to solve business problems using industry-standard machine learning frameworks and tools such as scikit‑learn, PyTorch, Tensor Flow, and Keras, combined with IBM tools and our AI application suites. You will prepare, process, and analyze data to deliver insight, build predictive models, and provide data‑driven recommendations to stakeholders. In your role, you may be responsible for:

• Developing, implementing, and validating machine learning models including supervised and unsupervised learning algorithms, deep learning architectures, and ensemble methods with a focus on scalable solutions for big data
• Building end‑to‑end data processing pipelines using tools such as Apache Spark, Pandas, and Num Py to cleanse, transform, and integrate data from multiple sources in an efficient and reusable manner
• Working in an Agile, collaborative environment, partnering with other data scientists, machine learning engineers, consultants and data engineers of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors
• Leveraging data processing and workflow orchestration tools such as Apache Airflow, Databricks, or similar platforms to automate model training and deployment workflows
• Communicating with internal and external clients to understand and define business needs and appropriate machine learning techniques to provide analytical solutions
• Evaluating model performance using industry‑standard metrics, conducting A/B testing, and communicating the results to technical and non‑technical audiences
• Utilizing version control (Git) and MLOps best practices to ensure reproducibility and collaboration

These positions are anticipated to start in 2026. We have positions opened in the Baton Rouge, Louisiana Client Innovation Center.

Preferred Education

Bachelor's Degree

Required Technical And Professional Expertise

• Strong fundamentals in Mathematics, Statistics, and Computer Science (algorithms, data structures)
• Proficiency in Python (preferred) or another mathematical/statistical programming language (MATLAB, R) for data science and machine learning, including experience with data/ml libraries such as scikit‑learn, Pandas, Num Py, and Matplotlib/Seaborn
• Hands‑on experience with at least one deep learning framework (Tensor Flow, PyTorch, or Keras)
• Practical understanding of machine learning algorithms including regression, classification, clustering, and dimensionality reduction techniques
• Experience with data processing and manipulation of large datasets using SQL and Python‑based tools
• You're great at solving problems by looking at things differently, debugging, troubleshooting, and designing & implementing solutions to complex technical issues.

Preferred Technical And Professional Experience

• Experience with distributed computing frameworks such as Apache Spark for large‑scale data processing, and experience constructing usable datasets from multiple structured and unstructured data sources using ETL/ELT processes
• Familiarity with MLOps tools and practices including model versioning, experiment tracking (MLflow, Weights & Biases), and deployment pipelines
• Understanding of cloud‑based machine learning platforms (AWS Sage Maker, Azure Machine Learning, Google Vertex AI)

Seniority level

Mid-Senior level

Employment type

Full‑time

Job function

Engineering and Information Technology

Industries

IT Services and IT Consulting

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