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Data Analyst

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Onsite

Data Analyst

Bavya Health Services Pvt Ltd

Data Analyst

Skills

SQL QueriesData MiningPythonData ScienceData VisualizationKnowledge ManagementNumPypandasRData AnalysisPower BI

9 days ago

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Important information


Contract type:

Permanent

Location:

Andhra Pradesh, India

Work mode:

Onsite

Published on:

13 October 2026

What they need


About the Role

We are seeking a Data Analyst with a minimum of 2 years of relevant experience in data analytics, business intelligence, public health, healthcare, monitoring and evaluation, or a related field. The role will primarily focus on data management, analysis, Power BI dashboard development, reporting, Python-based data processing, data quality, and programme monitoring.

The candidate will work closely with programme and senior analytics teams to transform programme data into accurate, meaningful, and actionable information. The role covers the data analytics lifecycle from data preparation and quality checking to visualization, reporting, interpretation, and programme performance monitoring.

Key Responsibilities

· Data Understanding & Programme Requirements: Understand programme objectives, indicators, workflows, reporting requirements, and data sources. Work with programme and M&E teams to understand routine analytical and reporting needs and translate defined requirements into appropriate datasets, indicators, visualizations, and reports.

· Data Preparation & Management: Collect, consolidate, clean, transform, and organize data from multiple sources. Work with structured and semi-structured datasets and prepare analysis-ready datasets for dashboards, reports, and analytical assessments.

· Power BI Dashboard Development: Develop and maintain interactive Power BI dashboards and reports. Create appropriate data models, calculated measures, visualizations, filters, drill-downs, and KPIs. Develop DAX measures and support dashboard testing, validation, user feedback, and continuous improvement.

· Data Analysis & Interpretation: Conduct descriptive and intermediate-level analysis to identify trends, patterns, relationships, variations, and gaps. Compare programme performance across time, locations, facilities, or population groups and support senior analysts in advanced statistical and epidemiological analysis.

· Python-Based Data Processing: Use Python for data cleaning, manipulation, transformation, merging, validation, routine analysis, and automation. Develop reusable scripts for repetitive data-processing activities and support advanced analytical workflows.

· ETL & Data Integration: Support ETL processes to extract, transform, validate, and integrate data from multiple sources. Help maintain reliable and analysis-ready datasets for dashboards and reports.

· Data Quality & Validation: Conduct routine data-quality checks for completeness, consistency, accuracy, duplication, missing values, and outliers. Identify data-quality issues, communicate gaps to relevant teams, and validate dashboard and report outputs.

· Analytical Reporting: Prepare analytical reports, programme performance reports, dashboards, charts, tables, and presentations. Summarize key findings clearly and ensure reports are accurate, timely, and aligned with programme requirements.

· Automated Reporting & Data Updates: Support automated or semi-automated processes for routine data preparation, dashboard refreshes, and report generation. Identify opportunities to reduce repetitive manual reporting.

· Programme Performance Monitoring: Monitor programme indicators through dashboards and analytical reports. Identify performance gaps, variations, emerging trends, and areas requiring attention, and provide data-based observations to programme teams.

· Stakeholder & Team Support: Work with programme, M&E, data, and field teams to resolve routine analytical and reporting requirements. Explain dashboard outputs and analytical findings to non-technical users and work under the guidance of senior analysts on complex assignments.

· Documentation & Knowledge Management: Maintain documentation for datasets, data dictionaries, indicator definitions, dashboard calculations, analytical methods, and reporting processes. Support standardization of data-processing and reporting procedures.

· Continuous Learning & Improvement: Keep up to date with Power BI, Python, data analytics, data visualization, and public health analytics. Identify opportunities to improve dashboards, reports, data processes, and analytical workflows.

Required Qualifications & Technical Skills

  1. Experience: Minimum 2 years of relevant hands-on experience in data analysis, business intelligence, public health analytics, healthcare analytics, monitoring and evaluation, or a related field.

  2. Power BI: Good hands-on experience developing Power BI dashboards, reports, visualizations, KPIs, filters, and data models.

  3. DAX: Working knowledge of DAX for calculated measures, calculated columns, time-based analysis, and analytical indicators.

  4. Python: Working knowledge of Python for data manipulation, cleaning, transformation, merging, analysis, and automation. Experience with Pandas and NumPy is desirable.

  5. SQL & Data Management: Working knowledge of SQL, database concepts, data extraction, joins, filtering, aggregation, and data transformation.

  6. Data Analysis: Strong analytical ability with experience identifying trends, patterns, relationships, discrepancies, and programme performance gaps.

  7. Data Quality: Understanding of data-quality concepts including completeness, consistency, accuracy, validation, duplication, missing data, and outlier identification.

  8. Public Health / Programme Data: Experience working with public health, healthcare, M&E, development-sector, or programme datasets is an advantage.

  9. Excel: Strong proficiency in MS Excel, including PivotTables, lookup functions, conditional logic, data cleaning, charts, and analytical functions.

  10. Communication: Ability to communicate analytical findings clearly through dashboards, reports, presentations, and discussions with technical and non-technical stakeholders.

Preferred Qualifications

· Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Public Health, Epidemiology, Mathematics, Economics, Health Informatics, or another quantitative discipline.

· Experience working with public health or healthcare information systems.

· Familiarity with monitoring and evaluation frameworks and programme indicators.

· Experience with statistical analysis using Python, R, SPSS, or similar tools.

· Basic understanding of epidemiology and public health indicators.

· Exposure to GIS/spatial data analysis is desirable but not mandatory.

· Experience working with APIs or integrating data from multiple systems is an advantage.

Core Technical Skills

Power BI | DAX | Python | Pandas | SQL | ETL | Excel | Data Cleaning | Data Validation | Data Modelling | Data Visualization | Analytical Reporting | Public Health Data | Monitoring & Evaluation

Key Attributes

· Strong analytical and problem-solving skills

· Good attention to detail and data accuracy

· Ability to understand complex datasets and programme requirements

· Strong data visualization and reporting skills

· Good communication and documentation skills

· Ability to work independently on routine analytical assignments

· Willingness to learn advanced analytics and data science techniques

Ability to work collaboratively with programme and technical teams

Pay: ₹306,000.00 - ₹700,000.00 per year

Benefits:

  • Flexible schedule
  • Provident Fund

Work Location: In person

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