Data Scientist
Owens & Minor (company site, opens in a new tab)On-siteDirect career pageEst. 10–22 LPA
Posted on 31 Aug
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Job description
Structured overview of role & requirements
About This Role
- Develop, optimize, and deploy machine learning models focused on time series forecasting and predictive analytics.
- Build and maintain data pipelines and warehouses using Python, PySpark, SQL, and cloud platforms like Google Cloud and Palantir Foundry to support scalable data integration and analytics.
- Continuously evaluate and improve model performance using metrics such as MAPE, RMSE, and R², collaborating with business stakeholders to align models with user expectations and business goals.
Minimum Requirements
- Proficiency in Python, PySpark, and SQL; strong experience with time series forecasting models including ARIMA, Prophet, LSTMs.
- Experience with data model optimization, feature engineering, and performance evaluation using ML metrics.
- Hands-on experience with cloud computing (Google Cloud) and data integration tools like Boomi, SnapLogic, SSIS, or Palantir.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in large-scale data integration projects and complex ETL/data transformation processes.
- Skilled in operating cloud-based ML platforms and automation tools such as AutoAI and Google Colab.
- Able to translate complex data science concepts into actionable business insights, indicating strong communication with cross-functional teams.