Data Scientist/Data Analyst - Python/Machine Learning
First seen by Alion on Sep 7, 2026.
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.
Skills
Data Science, Machine Learning, Python, SQL, NLP, Generative AI, Data Scientist, Data Analyst, Predictive Modeling