Data Scientist: Time-Series ML & Cloud Data Pipelines

Halyard Health; Glen Allen (VA); On-site; USD 110,000 - 117,000; Full time

Job summary

Owens & Minor is seeking a Data Scientist with a strong ML and data engineering background to build and optimize models, focusing on time series forecasting and predictive analytics. The role requires Python, PySpark, SQL, and experience with cloud platforms and data integration tools.

You will drive data-driven decisions across large-scale data projects, partnering with stakeholders to deliver production-ready solutions and measurable business impact.

Qualifications

• Strong background in ML, data engineering, and model optimization.
• Proficient in Python, PySpark, and SQL.
• Experience with time series forecasting and feature engineering.
• Familiarity with cloud platforms and data integration tools.

Responsibilities

• Develop and optimize machine learning models with a focus on time series forecasting and predictive analytics.
• Feature engineering and data model optimization to enhance model accuracy.
• Continuously evaluate model performance using metrics such as MAPE, RMSE, R².
• Build and implement data pipelines using PySpark, SQL, and cloud-based solutions.
• Work on large-scale data integration projects using Boomi, SnapLogic, SSIS, or Palantir.
• Utilize Palantir Foundry, Google Cloud, AutoAI, and Google Colab for data modeling and processing.
• Design and maintain data warehouse solutions to support analytics.
• Perform complex data transformations using SQL.
• Collaborate with stakeholders to align models with business objectives.
• Deploy, monitor, and improve machine learning models in production.
• Communicate findings effectively to technical and non-technical audiences.

Skills

Python

PySpark

SQL

Time series forecasting

Feature engineering

Model evaluation metrics

Data pipelines

Tools

Boomi

SnapLogic

SSIS

Palantir Foundry

Google Cloud

Job description

Owens & Minor is seeking a Data Scientist with a strong ML and data engineering background to build and optimize models, focusing on time series forecasting and predictive analytics. The role requires Python, PySpark, SQL, and experience with cloud platforms and data integration tools.

You will drive data-driven decisions across large-scale data projects, partnering with stakeholders to deliver production-ready solutions and measurable business impact.