Role: Team Lead - Data & AI

Employment Type: Full-Time

Experience: 5-8 Years

Location: New Delhi (On-site)

About the Role:

We are looking for a hands-on Technical Manager, Data & AI, who can build and lead our data department from the ground up. The role requires someone who can manage teams while also understanding and driving the technical work from data scraping and pipeline development to analytics, data science, AI/ML models and deployment. You will lead three specialized teams: Data Generation & Scraping, Data Analytics and Data Science and be responsible for building reliable data systems, improving data quality, developing AI-led solutions and ensuring projects move from problem statement data model deployment measurable outcome & insights. The ideal candidate should be equally comfortable managing people, reviewing technical architecture, solving complex data problems and delivering under tight timelines typical of political consulting.

Teams Under this Role:

1. Data Generation & Scraping Team:

Oversee web scraping, field data collection, social media harvesting and OSINT operations.

Set and enforce data quality, sourcing ethics and legal compliance standards.

Manage tools and infrastructure: Scrapy, Selenium, Apify, custom crawlers, API integrations.

2. Data Analysts Team:

Manage reporting pipelines, dashboards and constituency/ward-level analysis.

Ensure insights are translated into clear, actionable political strategy.

Oversee tooling: Excel, Power BI, Tableau, SQL, Google Looker Studio.

3. Data Science & AI Team:

Lead model development, experimentation and deployment cycles.

Bridge the gap between raw data pipelines and strategic AI outputs.

Manage tech stack: Python, R, TensorFlow/PyTorch, HuggingFace, LangChain, AWS/GCP/Azure.

Key Responsibilities:

1. Strategic Leadership:

Design and own the data strategy aligned with political campaign cycles and consultancy goals.

Build scalable data infrastructure from ingestion to insight delivery.

Advise leadership on data-driven political strategy and risk assessment.

2. AI & Machine Learning:

LLM for Retrospective Election Analysis:

– Develop LLM pipelines to analyse historical voting patterns, demographic shifts and electoral correlations.

Sentiment Analysis:

– Build real-time sentiment pipelines from social media, news and survey data.

Geospatial Data Mapping:

– Develop constituency-level geospatial visualisation and mapping models using GIS tools.

Database Management & Reporting:

– Oversee architecture of political data databases and build automated reporting systems.

New AI Use Cases:

– Identify and prototype emerging use cases like voter targeting, issue salience modelling and influence mapping.

3. Team Management:

Recruit, mentor and retain talent across all three data teams.

Define KPIs and OKRs for each team and ensure consistent delivery.

Foster a culture of intellectual curiosity, speed and rigour.

Manage inter-team dependencies and workload prioritisation during high-pressure election sprints.

4. Operations & Governance:

Ensure data governance and privacy compliance (IT Act, DPDP Act and electoral data regulations).

Manage vendor relationships, cloud costs and critical tooling decisions.

Build documentation standards and institutional knowledge frameworks.

QUALIFICATIONS & TECHNICAL REQUIREMENTS:

Education:

B.Tech / B.E. / M.Tech in Computer Science, Statistics, Mathematics, or a related field.

MBA is a plus, not a mandatory requirement.

Experience:

5–8 years of total experience in data roles.

Minimum 2 years in a leadership or team management capacity.

Proven experience in managing multi-functional data teams.