Birbhum
| Title | Description |
|---|---|
| Data Analysis & Interpretation | Collect, process, and analyze healthcare data from various hospital systems and digital platforms. Identify trends, correlations, and insights to support decision-making and hospital performance improvement. Prepare reports and dashboards highlighting key metrics and operational efficiencies. |
| AI & Predictive Analytics | Develop AI and machine learning models for predictive healthcare analytics and automation. Implement data-driven algorithms to improve patient management, diagnostics, and resource utilization. Collaborate with software and IT teams to integrate AI tools into hospital systems. |
| Data Management & Quality Control | Ensure accuracy, consistency, and security of large datasets from multiple sources. Maintain databases, perform data cleaning, and validate information integrity. Optimize data pipelines for real-time analytics and AI integration. |
| Visualization & Reporting | Design interactive dashboards and visualizations using tools like Power BI, Tableau, or Python (Matplotlib/Seaborn). Present findings and insights to management and medical professionals in an understandable format. |
| Research & Innovation | Explore emerging AI techniques and data analytics models relevant to healthcare and hospital operations. Support research initiatives by providing analytical models and insights from medical and administrative data. |
| Title | Description |
|---|---|
| Technical Skills: | Strong knowledge of data analysis tools like Python (NumPy, Pandas, Scikit-learn) or R. Experience with machine learning algorithms, data visualization, and statistical modeling. Familiarity with SQL/NoSQL databases and data pipeline tools (ETL). Proficiency in AI frameworks such as TensorFlow, Keras, or PyTorch. Understanding of cloud-based analytics platforms (AWS, Google Cloud, Azure). |
| Soft Skills: | Analytical mindset with attention to accuracy and detail. Strong problem-solving and logical reasoning abilities. Effective communication for presenting technical insights to non-technical stakeholders. Collaboration with interdisciplinary teams including doctors, developers, and management. Curiosity for innovation and continuous learning in AI and data science. |
| Title | Description |
|---|---|
| Educational Qualification: | Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Artificial Intelligence, or related field. |
| Experience: | 2–5 years of experience in data analytics, AI modeling, or machine learning applications, preferably in healthcare or IT. |
| Preferred Background: | Prior exposure to hospital analytics, digital health projects, or AI-driven systems will be an advantage. |
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