Jobs via Dice
Associate Data Scientist - Entry Level (Baton Rouge, LA)
Jobs via Dice, Baton Rouge, Louisiana, us, 70873
Associate Data Scientist - Entry Level (Baton Rouge, LA)
IBM Consulting is hiring an entry‑level Associate Data Scientist to join our client innovation centers in Baton Rouge, Louisiana. The role focuses on solving business problems with industry‑standard machine learning techniques and delivering data‑driven recommendations to stakeholders.
Responsibilities
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.
Qualifications
Bachelor’s Degree in Computer Science, Mathematics, Statistics, or a related technical field.
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.
Preferred Technical 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).
About IBM Consulting IBM Consulting is IBM’s consulting and global professional services business, providing strategy, experience, technology, and operations services to clients worldwide. The consulting team is focused on accelerating client businesses through the power of collaboration and responsible technology.
Equal Opportunity Employer IBM is proud to be an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, or any other characteristics protected by law. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
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Responsibilities
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.
Qualifications
Bachelor’s Degree in Computer Science, Mathematics, Statistics, or a related technical field.
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.
Preferred Technical 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).
About IBM Consulting IBM Consulting is IBM’s consulting and global professional services business, providing strategy, experience, technology, and operations services to clients worldwide. The consulting team is focused on accelerating client businesses through the power of collaboration and responsible technology.
Equal Opportunity Employer IBM is proud to be an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, or any other characteristics protected by law. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
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