Data Scientist

360 Technology is seeking a **Data Scientist with DevOps and DataOps experience** to develop, deploy, and operationalize enterprise machine learning and analytics solutions. The ideal candidate will combine strong data science expertise with hands-on experience in MLOps, CI/CD, cloud platforms, and production data operations. **Key Responsibilities** * Develop machine learning, predictive analytics, and statistical models. * Perform data preparation, feature engineering, experimentation, and model evaluation. * Deploy and maintain models through scalable MLOps and DataOps pipelines. * Build CI/CD workflows for data science and machine learning applications. * Monitor model accuracy, data quality, performance, drift, and production reliability. * Collaborate with data engineers, business teams, architects, and DevOps professionals. * Automate cloud infrastructure, model deployment, testing, and release processes. **Required Skills** * Strong experience with Python, SQL, machine learning, and statistical modeling. * Experience with Pandas, Scikit-learn, TensorFlow, PyTorch, or similar frameworks. * Knowledge of Databricks, Snowflake, Spark, MLflow, or cloud machine learning platforms. * Experience with Azure DevOps, GitHub Actions, Jenkins, or GitLab CI/CD. * Familiarity with Docker, Kubernetes, Terraform, APIs, and cloud platforms. * Understanding of MLOps, DataOps, model monitoring, data governance, and production support. Candidates must be available to work **onsite in Dallas, Texas**.

Develop and operationalize enterprise machine learning and predictive analytics solutions. Build and maintain scalable MLOps and DataOps pipelines including CI/CD workflows and model monitoring.

Requires strong expertise in Python, SQL, and ML frameworks along with experience in cloud platforms and DevOps tools. Candidates must have a background in MLOps and be able to work onsite in Dallas, Texas.

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Python
• SQL
• Machine Learning
• Statistical Modeling
• Pandas
• Scikit-learn
• TensorFlow
• PyTorch
• Databricks
• Snowflake
• Spark
• MLflow
• Azure DevOps
• GitHub Actions
• Docker
• Kubernetes

• Data & Analytics
• Technology
• Software
• Engineering
• Science & Research

Expérience minimale

5+ ans

Postuler avant le

13 août 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Niveau d’expérience

Mid-Senior level

Mode de candidature

La candidature directe est offerte