IBM
Associate Data Scientist - Entry Level (Baton Rouge, LA)
IBM, Baton Rouge, Louisiana, us, 70873
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, TensorFlow, 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 NumPy 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, NumPy, and Matplotlib/Seaborn
Hands‑on experience with at least one deep learning framework (TensorFlow, 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 SageMaker, 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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Get AI-powered advice on this job and more exclusive features.
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, TensorFlow, 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 NumPy 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, NumPy, and Matplotlib/Seaborn
Hands‑on experience with at least one deep learning framework (TensorFlow, 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 SageMaker, 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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