Bhavuk Manocha
Co-founding a company in stealth. More soon.
Eight years of analytics before this: core banking at Slice, delivery planning at Flipkart, shopper analytics for Walmart at Tredence. Based in Bengaluru.
Record
2014–18
IIT (ISM) Dhanbad
B.Tech, Chemical Engineering
Chemical engineering: whatever goes into a system has to come out somewhere.
- Four years in Dhanbad; graduated May 2018
2018–20
Tredence
Business Analyst, then Senior, on Walmart US
Shopper analytics for Walmart US; ran the client relationship solo.
- Retail analytics for Walmart US, from the Bengaluru office
- Ran the US client relationship solo, including executive presentations
- Promoted from Business Analyst to Senior Business Analyst
2020–22
Flipkart
Planning Analyst
Capacity planning against the one-day delivery promise in metro cities.
- Planned against the one-day delivery promise in metro cities
- Automated daily and monthly planning, saving two days a cycle
2022–26
Slice
Senior Analyst to Analytics Manager, Core Banking
Led the core banking analytics pod through the move from fintech to small finance bank; owned the analytics hiring charter and a $200k AWS budget.
- Defined monthly transacting users and the cohort tracking behind board-level growth numbers
- Owned the hiring charter for the analytics org: 120+ interviews, and trained other interviewers
- Owned a $200k AWS analytics budget; auto-terminating EMR clusters kept the burn in check
- Promoted two people from the pod
- Named AI Pioneer twice
- Promoted from Senior Analyst to Lead Analyst to Analytics Manager
2026–
A company in stealth
Co-founder
Nothing further to disclose yet.
Selected work
TredenceThe expecting-mothers journey
$3,000 potential revenue per household
Modelled how expecting mothers shop for Walmart US, worth about $3,000 of potential revenue per household.
FlipkartOne-day delivery planning
30% to 80%
The one-day delivery SLA in metro cities went from 30% to 80%.
FlipkartPeak-sale fixes
7 days to 1
Automated diagnostics cut the time from spotting a problem to fixing it during peak sales from seven days to one. Daily and monthly planning was automated too, saving two days a cycle.
Slice, 2023–24RADAR, finance alerting
₹1.2L a day caught
One alerting framework for finance: 150+ alerts automated, false positives down 80%, issue detection 90% faster, and ₹1,000 Cr+ of historical accounting issues surfaced and resolved.
SliceAccounting V2, two-way reconciliation
0.01 tolerance
Loan-management and core-banking ledgers reconciled in both directions, closed T+1. SLAs up 150%, downtime down 60%, and 20+ Airflow DAGs at 99.99% on ₹50M a day of settlements across 10+ entities.
SliceTDS compliance under section 194N
₹3.04L refunded
Detection, refunds and tracking, end to end: 100% accuracy, zero penalties, about 30 hours a month saved.
SliceInvestor databook
$30M debt raise
Automated the due-diligence reporting behind a $30M debt raise. Weeks of work became hours, with no manual errors.
Slice, 2024AI across analytics
100+ hours a month
Co-founded the central AI pod and ran the first Cursor rollout with custom rules, plus Compliance GPT for checking marketing copy against RBI guidelines. 29 tickets resolved by AI, first response from an hour to 25 seconds, and the AI Pioneer award twice.
Toolkit
- Data systems
- AWS (S3, EMR, EC2), PySpark, Airflow DAGs, Delta Lake, ETL pipelines, Warehouse tuning
- Analytics
- SQL, Python and pandas, Superset, Tableau, A/B testing, Financial modelling
- Fintech
- Lending analytics, RBI regulatory reporting, Financial reconciliation, Unit economics (LTV, CAC, MAU)
- Leading teams
- Hiring across an analytics org, Mentoring and promotions, Budget ownership, Crisis management
- AI tooling
- LLM integration, Cursor with custom rules, Retrieval (RAG), n8n automation
Off the clock
- Badminton
- Weekend rallies, mostly.
- Strategy and RPGs
- Slow campaigns, fast saves.
- Reading
- Non-fiction by day, fiction by night.
- Travel
- Always mapping the next trip.
Find me on LinkedIn
or write to me at manocha.bhavuk