Data Scientist
Owens & Minor (company site, opens in a new tab)On-siteDirect career pageEst. 12–22 LPA
Posted on 31 Aug
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Job description
Structured overview of role & requirements
About This Role
- Develop and optimize machine learning models focusing on time series forecasting and predictive analytics with measurable business impact.
- Build and maintain data pipelines, perform feature engineering, and optimize models for accuracy and efficiency using Python, PySpark, SQL, and cloud-based tools.
- Lead large-scale data integration and transformation projects using tools like Boomi, SnapLogic, Palantir, and Google Cloud platforms, ensuring alignment with business objectives.
Minimum Requirements
- Proficiency in Python, PySpark, SQL, and experience in time series forecasting models (e.g., ARIMA, Prophet, LSTMs).
- Hands-on experience with data engineering, ETL, data pipelines, and data transformation including use of Boomi, SnapLogic, SSIS, or Palantir.
- Experience with cloud computing platforms, specifically Google Cloud tools like BigQuery and Vertex AI.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in implementing and optimizing machine learning models in production environments with strong grasp of evaluation metrics like MAPE, RMSE, and R².
- Skilled in large-scale data integration projects across varied tools and platforms including Palantir Foundry and Google Cloud.
- Capable of collaborating with cross-functional teams to translate business needs into ML and data pipeline solutions, demonstrating strong communication of technical concepts to non-technical stakeholders.