Data Analyst Intern - Artificial Intelligence Science

Aisensum builds AI teammates that move the P&L — revenue (ROI), time/cost (ROT), and quality/productivity (ROQ) — and deploy them in weeks, not months.

Who we want A fresh grad or final-year student (preferably Economics / Econometrics / Statistics / Mathematics / Data Science) who is strong on business thinking, comfortable with SQL & Python, and can translate messy data into decisions that affect revenue, margins, or productivity. Work on real client projects: turn raw transaction/CRM/kiosk data into actionable models, dashboards, and recommendations that drive measurable business outcomes.

Key Responsibilities

• Clean, merge, and QA multi-source datasets (CRM, POS, kiosks, Excel extracts).
• Write & optimise SQL (joins, aggregations, window functions).
• Descriptive analytics: cohorts, funnels, RFM/RFMP, conversion funnels.
• Build and validate logistic regression/propensity models; interpret results for business owners.
• Produce management-ready charts, short slide summaries, and one-line recommendations.
• Support Senior Ops/AI Science in data checks, UAT, and deployment monitoring.
• Document assumptions, edge-cases, and data quality issues.

Must-have skills

• Degree: Economics / Econometrics / Statistics / Math / Data Science (or equivalent).
• SQL: basic → intermediate (joins, group by, filters; window functions preferred).
• Python: Pandas / NumPy for data cleaning & analysis.
• Statistics: regression (logistic), hypothesis testing, distributions, sampling.
• Business sense: can answer — “what does this number mean for revenue, cost, or quality?”
• Clear written English and attention to detail.

Nice-to-have

• Experience with BI tools (Tableau / Power BI / Looker Studio).
• Coursework or projects in propensity modelling, pricing, and demand forecasting.
• Basic familiarity with Git or other version control systems.
• Exposure to real-world datasets (through internships, competitions, and capstone projects).

What you’ll learn

• Running end-to-end analytics for paying clients (not toy datasets).
• Turning models into decisions that affect ROI / ROT / ROQ.
• Exposure to deploying AI teammates (Daniel / Sasha / Nadia use-cases).

Internship details

• Duration: 3–6 months (flexible).
• Mode: Hybrid (preferably in Bogor/Jakarta).
• Start: [Month/Year] — specify on application.
• Stipend: As per institute/policy (will be communicated at offer stage).
• Assessment: Short coding/data test + short case discussion.

Skills: Data Analysis, Data Visualization, SQL