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About The Company
ThreatXIntel is a forward-thinking organization dedicated to leveraging data-driven insights to address complex societal challenges. With a focus on public health, socio-economic analysis, and innovative technological solutions, ThreatXIntel aims to empower policymakers, healthcare providers, and community stakeholders with actionable intelligence. Our commitment to excellence and innovation positions us at the forefront of data analytics and predictive modeling in the public sector. We foster a collaborative environment that encourages continuous learning, creativity, and impactful work that makes a real difference in communities worldwide.
About The Role
We are seeking a highly skilled Freelance Data Engineer / Machine Learning Engineer to join our team on a project basis. The ideal candidate will be responsible for designing and implementing an end-to-end data pipeline and developing a predictive analytics system centered on life expectancy modeling. This role involves working with diverse public health and socio-economic datasets, transforming raw data into meaningful insights, and building models that can forecast life expectancy trends across different regions and communities.
The successful candidate will possess a strong background in data engineering, big data processing, and machine learning, with demonstrated experience handling real-world datasets. This position offers an exciting opportunity to contribute to impactful projects that influence health policies and community interventions, utilizing cutting-edge technologies and analytical approaches.
Qualifications
Candidates should have a solid foundation in Python and SQL, with extensive experience in building scalable data pipelines and ETL processes. Familiarity with big data tools such as Apache Spark and Databricks is essential. Hands-on experience with machine learning frameworks like scikit-learn, including feature engineering and model evaluation, is required. A strong understanding of data modeling, transformations, and working with public datasets and APIs is vital. Candidates should also possess good knowledge of data pipeline architectures, statistical analysis, and predictive modeling techniques. Prior experience in public health or healthcare analytics, geospatial data analysis, and cloud platforms (AWS, Azure, GCP) will be considered advantageous.
Responsibilities
- Design and develop scalable data pipelines using Python, SQL, and Apache Spark to process large volumes of public health and socio-economic data.
- Ingest data from various sources including APIs, government datasets, and healthcare repositories, ensuring data quality and consistency.
- Create a multi-layer data architecture comprising Bronze (raw data), Silver (cleaned data), and Gold (aggregated/feature-ready data) layers for efficient data management and analysis.
- Perform extensive data transformation, cleaning, joins, and aggregations at regional and community levels to prepare datasets for modeling.
- Develop key health indicators such as mortality rates, poverty and unemployment metrics, healthcare provider density, and food accessibility indices.
- Construct composite indices like the Economic Hardship Index and Health Access Index to capture complex socio-economic factors influencing life expectancy.
- Build and evaluate predictive models using machine learning algorithms such as Random Forests and Regression techniques, analyzing feature importance to identify key life expectancy drivers.
- Design and implement an interactive Life Expectancy Simulator that enables scenario-based analysis, such as assessing the impact of healthcare improvements or poverty reduction strategies.
- Create comprehensive dashboards and visualizations using Power BI, Streamlit, and Folium to communicate insights effectively and highlight disparities across communities.
- Generate detailed reports and presentations to support policy recommendations and strategic planning based on analytical findings.
Benefits
As a freelance team member, you will have the opportunity to work on impactful projects that influence public health policies and community well-being. You will gain exposure to diverse datasets, advanced data engineering techniques, and machine learning applications in a real-world context. Flexibility in work hours and location allows for a balanced work environment. Additionally, you will collaborate with a multidisciplinary team of data scientists, public health experts, and policy advisors, fostering professional growth and expanding your expertise in social impact analytics. ThreatXIntel values innovation, continuous learning, and contributions that make a tangible difference in society.
Equal Opportunity
ThreatXIntel is an equal opportunity employer committed to fostering an inclusive environment for all employees and contractors. We celebrate diversity and are dedicated to creating a workplace that respects and values individual differences. We do not discriminate based on race, ethnicity, gender, age, sexual orientation, disability, or any other protected characteristic. We believe that diverse perspectives and experiences drive innovation and excellence, and we welcome applicants from all backgrounds to join our mission of leveraging data for social good.
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