Principal Data Scientist#26-02628

Bentonville, AR

Onsite Job Description

Advanced experience designing, building, and deploying machine learning solutions in production environments at enterprise scale.

Strong expertise in Python and modern machine learning frameworks such as Scikit-Learn, TensorFlow, PyTorch, XGBoost, or similar technologies.

Deep experience developing machine learning models including:

Random Forest

Isolation Forest

Classification Models

Regression Models

Clustering Algorithms

Anomaly Detection Frameworks

Predictive Analytics and Forecasting Models

Proven track record operationalizing AI/ML solutions from experimentation through production deployment and monitoring.

Strong understanding of feature engineering, model evaluation, model explainability, and MLOps best practices.

Experience building scalable ML pipelines and workflows using orchestration frameworks such as Airflow, Kubeflow, MLFlow, or similar platforms.

Strong data engineering foundations including SQL, data modeling, ETL/ELT design, and distributed data processing.

Experience working with BigQuery, Spark, DBT, Databricks, or comparable cloud-scale analytical platforms.

Experience with cloud-native architectures and services across Azure, Google Cloud Platform (GCP), AWS, or hybrid cloud environments.

Hands-on experience developing and deploying microservices, REST APIs, containerized applications, and Kubernetes-based solutions.

Experience with CI/CD practices and software engineering principles for scalable AI platform development.

Strong knowledge of NLP, semantic search, vector embeddings, Retrieval-Augmented Generation (RAG), LLMs, and Generative AI applications.

Experience building intelligent systems leveraging embeddings, vector databases, and modern AI agent frameworks is highly preferred.

Demonstrated ability to lead technical strategy while influencing cross-functional stakeholders across engineering, product, analytics, and business organizations.

Exceptional problem-solving, analytical thinking, and communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences.

Proven ability to mentor teams, establish technical standards, and drive adoption of AI/ML best practices across large organizations.

Passion for innovation and building the future of intelligent audit, analytics, and decision-support platforms.