Data Scientist

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Skills you'll use

What you'll do

• Develop and optimize machine learning models with a focus on time series forecasting and predictive analytics.
• Perform feature engineering and data model optimization to enhance model accuracy and efficiency.
• Continuously evaluate model performance using metrics such as MAPE, RMSE, R², and adjust strategies accordingly.
• Build and implement data pipelines using PySpark, SQL, and cloud-based solutions for seamless data integration.
• Work on large-scale data integration projects, leveraging tools such as Boomi, SnapLogic, SSIS, or Palantir to extract, transform, and load data.
• Utilize Palantir Foundry, Google Cloud, AutoAI, and Google Colab for data modeling, processing, and automation.
• Design and maintain data warehouse solutions to support advanced analytics and business intelligence.
• Perform complex data transformations using SQL queries and data objects to support AI/ML-driven initiatives.
• Collaborate closely with business stakeholders to ensure models align with user expectations and business objectives.
• Deploy, monitor, and continuously improve machine learning models in production environments.

Who can apply

• Proficiency in Python, PySpark, and SQL for data analysis, feature engineering, and model development.
• Expertise in time series forecasting models, including ARIMA, Prophet, LSTMs, and ML-based approaches.
• Strong experience in data model optimization, feature engineering, and performance evaluation.
• Deep understanding of ML model evaluation metrics and best practices in improving model accuracy.
• Hands-on experience in data engineering, working on data pipelines, ETL, and data transformation projects.
• Experience using Boomi, SnapLogic, SSIS, or Palantir for data integration.
• Proficiency in cloud computing, particularly Google Cloud (BigQuery, Vertex AI, Cloud Functions, etc.).
• Experience with Palantir Foundry for data processing, analysis, and visualization.
• Ability to optimize and query large-scale datasets using data lakes and relational databases.
• Familiarity with AutoAI for automated model selection and hyperparameter tuning.

About Owens & Minor

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