We’re hiring a full-time, on-site AI Data & Automation Analyst based in Chandigarh. This role owns the end‑to‑end marketing analytics stack for multiple performance marketing teams (VSL, Leadgen, E‑com), from ingesting raw campaign data into our database to building dashboards and automated reports that drive daily decisions. You’ll sit between data, marketing, and product, making sure performance data is accurate, accessible, and easy for the team to act on.
You will design and maintain core data models, automate recurring analysis and reporting, and use AI/ML-powered tools to uncover trends, optimize funnels, and improve user acquisition and revenue outcomes.
Key Responsibilities
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Own the marketing analytics data stack built on Supabase (Postgres), including schema design, data modeling, and query performance for reporting and dashboards.
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Design, build, and maintain dashboards (e.g., in Loveable/React or BI tools) that give clear visibility into performance across campaigns, niches, and teams.
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Build and maintain automated data pipelines and scripts to ingest campaign and performance data from platforms like Lookfinity and Meta/Facebook Ads Library into Supabase.
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Clean, transform, and aggregate large marketing datasets using SQL and Python (or similar) for regular reporting and ad‑hoc analysis.
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Apply statistical techniques (hypothesis testing, basic regression, experiment/A/B test analysis) to evaluate campaigns and funnels, and recommend optimizations.
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Support and improve analytics for creative and copy workflows (e.g., dashboards for script assignments, approvals, and performance tracking).
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Implement and monitor data quality checks, documentation, and basic governance so stakeholders can trust the numbers in dashboards and reports.
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Collaborate closely with marketing, creative, and tech teams to turn open questions into concrete analysis, and present findings in a clear, actionable way.
Qualifications & Skills
- 1–3+ years of experience in data analytics or data automation, ideally in performance marketing, growth, or a similarly data-driven environment.
- Strong analytical skills with the ability to interpret complex datasets and turn them into clear insights and recommendations.
- Solid foundation in Statistics and experimentation (hypothesis testing, experiment/A/B test design, funnel/cohort concepts).
- Proficiency in SQL (preferably on PostgreSQL) and comfort with data modeling for reporting and analytics.
- Experience with a scripting language like Python (or JavaScript/TypeScript) for building pipelines, automations, and API integrations.
- Familiarity with BI/dashboard tools (Power BI, Tableau, Looker Studio, or React/Loveable dashboards).
- Interest or experience with AI/ML concepts and LLM tools used in analytics, reporting, or marketing optimization is a strong plus.
- Clear communication skills and comfort working with both technical and non‑technical stakeholders in a fast-paced, experiment-heavy environment.
