INClusive Minds - Data Scientist/Data Analyst - Python/Machine Learning

About Us:

We are looking for a dynamic Data Scientist / Data Analyst to transform raw data into actionable insights that influence political strategies and decision-making.

Key Responsibilities:

1. Data Analysis &

• Reporting:
• Analyse voter demographics, election results, polling, social media, and public sentiment data.
• Conduct pre-poll and post-poll analysis to identify actionable insights.
• Build dashboards, visualisations, and reports for clients and internal stakeholders.

2.

Predictive

Modelling &

• Machine Learning:
• Build predictive models for election outcomes, voter behaviour, sentiment trends, and campaign impact.
• Apply ML techniques such as forecasting, clustering, segmentation, and recommendation systems.
• Develop data-driven solutions for targeted campaign strategies.

3.

Statistical

Analysis &

• Insights:
• Apply statistical methods to identify voting patterns, demographic trends, and campaign impact.
• Conduct A/B testing and other analytical methods to evaluate and optimise campaign strategies.

4. Collaboration &

• Stakeholder Management:
• Work closely with political analysts, campaign managers, and technology teams to translate data into strategic insights.
• Present complex analytical findings in a clear, concise, and actionable manner to non-technical stakeholders.

5. Data Strategy &

• Innovation:
• Identify and integrate new data sources to strengthen analytical capabilities.
• Explore and implement emerging data science, AI, and GenAI technologies to solve business and campaign problems.
• Stay updated with the latest tools, technologies, and analytical methodologies.

Required Skills:

• Strong analytical aptitude with knowledge of statistics, mathematical modelling, pattern recognition, and problem-solving.
• Proficiency in Python, SQL, Excel, and Power BI/ Tableau.
• Understanding of machine learning, predictive modelling, forecasting, and clustering.
• Exposure to Hadoop, Spark, or similar big-data technologies.
• Experience with NLP libraries such as NLTK, spaCy, or Hugging Face.
• Strong communication, collaboration, and stakeholder-management skills.

Preferred Qualifications:

• Experience building end-to-end, small-scale GenAI projects.
• Exposure to tools/frameworks such as LangGraph, OpenAI, Hugging Face, Ollama, Sloth, bitsandbytes, etc.
• Experience with backend frameworks such as FastAPI, Uvicorn, or similar.
• Exposure to frontend frameworks such as Flask, Django, React, or similar.