Interesting Job Opportunity: Think41 - Data Analyst - Python

Location :

Think41, HSR layout Bangalore

Job Type :

Full-Time

About Think41

Think41 is an early-stage startup with a mission to build a leading technology consulting firm providing Gen AI Services & Solutions. Our leadership team previously built HashedIn, a cloud services & solutions company acquired by Deloitte in 2021, now a cornerstone of Deloitte Engineering. With early funding established, Think41 is looking to assemble an all-star engineering team passionate about Gen AI tools and ecosystems.

Role Summary

Support day-to-day retail analytics across sales, margin, assortment, pricing/promotions, inventory and returns. Build reliable dashboards, write clean SQL/Python, run ad-hoc deep dives, and help evaluate experimentspartnering closely with business, product, and :

• Build and maintain executive and team dashboards (Power BI/Tableau/Looker Studio); automate recurring reports; document metric definitions.
• Write performant SQL (joins, window functions, CTEs) and use Python (pandas/NumPy) for wrangling and QC; publish reusable queries/views.
• Run deep dives on price & promo performance, category/basket KPI shifts, stockouts/returns, conversion funnels and cohorts; recommend next actions.
• Assist with A/B and holdout analysesdefine metrics, sanity checks, readouts, and learnings.
• Partner with product/marketing on GA4/GTM tracking; validate tags and reconcile web/app data with warehouse tables.
• Monitor data freshness/accuracy, raise issues, and maintain playbooks/SOPs.
• Under guidance, review low-risk AI-agent suggestions (e.g., minor promo tweaks, exception queues), record rationale, and escalate edge cases.
  

Must-have Qualifications

• 23 years in analytics/BI; retail/e-commerce/CPG exposure preferred.
• Strong SQL; solid Excel; experience with at least one BI tool (Power BI/Tableau/Looker Studio).
• Working Python (pandas/NumPy) for data prep and analysis; Git basics helpful.
• Comfort with funnels/cohorts, conversion/AOV, margin basics, and interpreting KPI movements in a retail context.
• Fundamentals of experimentation and descriptive statistics; ability to explain assumptions/limitations.
• Clear communication : concise summaries, structured storytelling, and stakeholder management.
  

Nice-to-have (aspirational, Not Mandatory)

• GA4/GTM implementation audits
• Cloud DW exposure (BigQuery/Snowflake/Redshift) and basic dbt/Airflow concepts.
• Forecasting/promo-uplift basics (Prophet/ARIMA) and simple optimization intuition (assortment/inventory).
• Experience with QA of tracking, metric governance, and lightweight scripting for automation.
  

(ref:hirist.tech)