Freelance Data Engineer / ML Engineer (Public Health Analytics)

Role Overview

We are looking for a highly skilled Freelance Data Engineer / Machine Learning Engineer to build an end-to-end data pipeline and predictive analytics system focused on life expectancy modeling using public health and socio-economic data .

The ideal candidate should have strong experience in data engineering, big data processing, and machine learning , with the ability to work on real-world datasets and derive actionable insights .

Key Responsibilities

Data Engineering

• Build scalable data pipelines using Python, SQL, and Apache Spark
• Ingest data from APIs and public datasets (Census, healthcare, etc.)
• Design multi-layer architecture:
  • Bronze (raw data)
  • Silver (cleaned data)
  • Gold (aggregated/feature-ready data)
• Perform data transformation, joins, and aggregation at regional/community level

Feature Engineering

• Develop key health indicators such as:
  • Mortality rates
  • Poverty & unemployment rates
  • Healthcare provider density
  • Food accessibility metrics
• Build composite indices like:
  • Economic Hardship Index
  • Health Access Index

Machine Learning

• Develop predictive models using scikit-learn (Random Forest, Regression)
• Evaluate models using:
  • R² Score
  • RMSE
• Perform feature importance analysis to identify key drivers of life expectancy

Simulation & Insights

• Build an interactive Life Expectancy Simulator
• Enable scenario-based analysis (e.g., impact of poverty reduction, healthcare improvements)
• Provide recommendations for policy and intervention strategies

Visualization & Reporting

• Create dashboards using Power BI and Streamlit
• Develop geospatial visualizations using Folium
• Highlight disparities across communities and generate insights reports

Required Skills & Experience

• Strong experience in:
  • Python, SQL
  • Data Engineering & ETL pipelines
  • Big Data tools (Spark, Databricks)
• Hands-on experience with:
  • Machine Learning (scikit-learn)
  • Feature engineering & model evaluation
• Experience working with:
  • Public datasets / APIs
  • Data modeling & transformations
• Good understanding of:
  • Data pipelines (Bronze/Silver/Gold architecture)
  • Statistical analysis and predictive modeling

Nice to Have

• Experience in public health / healthcare analytics
• Knowledge of geospatial data analysis
• Experience building interactive dashboards or simulators
• Exposure to cloud platforms (AWS / Azure / GCP)