Note: The job is a remote job and is open to candidates in USA. Precision Technologies is a company that focuses on technology solutions, and they are seeking a Data Scientist to join their team. The role involves collecting and analyzing data, developing machine learning models, and collaborating with various stakeholders to provide analytical solutions.
Responsibilities
- Collect, clean, preprocess, and analyze structured and unstructured data from multiple sources
- Develop, train, evaluate, and deploy Machine Learning models for classification, regression, clustering, forecasting, and recommendation systems
- Perform exploratory data analysis (EDA), statistical modeling, hypothesis testing, and feature engineering
- Build predictive analytics solutions using supervised and unsupervised machine learning techniques
- Develop data visualization dashboards and reports using Power BI, Tableau, or Python visualization libraries
- Collaborate with business stakeholders, Data Engineers, Product Managers, and Software Engineers to translate business problems into analytical solutions
- Optimize machine learning models for scalability, accuracy, and production deployment
- Work with large-scale datasets using distributed computing frameworks such as Spark and Databricks
- Deploy machine learning models using MLOps best practices and cloud platforms such as AWS, Azure, or GCP
- Monitor model performance, retrain models, and continuously improve predictive accuracy
- Document analytical methodologies, model performance, and technical solutions while supporting production environments
Skills
- Collect, clean, preprocess, and analyze structured and unstructured data from multiple sources
- Develop, train, evaluate, and deploy Machine Learning models for classification, regression, clustering, forecasting, and recommendation systems
- Perform exploratory data analysis (EDA), statistical modeling, hypothesis testing, and feature engineering
- Build predictive analytics solutions using supervised and unsupervised machine learning techniques
- Develop data visualization dashboards and reports using Power BI, Tableau, or Python visualization libraries
- Collaborate with business stakeholders, Data Engineers, Product Managers, and Software Engineers to translate business problems into analytical solutions
- Optimize machine learning models for scalability, accuracy, and production deployment
- Work with large-scale datasets using distributed computing frameworks such as Spark and Databricks
- Deploy machine learning models using MLOps best practices and cloud platforms such as AWS, Azure, or GCP
- Monitor model performance, retrain models, and continuously improve predictive accuracy
- Document analytical methodologies, model performance, and technical solutions while supporting production environments
Company Overview