Business systems
Salesforce CPQ rules, governance, specs, UAT, release handoffs.
Technical BA · AI business analyst · CRM & data
Technical BA & AI business analyst
Before Ireland, I spent six years at Infoblox in Salesforce CPQ, CRM governance, BI, and sales operations: 200+ quotes reviewed daily, 60K+ accounts and SKUs governed, and 95% order-to-cash accuracy on the White Glove path. I blend business analysis, machine learning, and business acumen to help teams turn messy operations into clearer decisions, cleaner workflows, and measurable outcomes.
“I had the pleasure of working with Subhankar at Infoblox, where his proactive approach, attention to detail, and exceptional time management really stood out. Despite joining just before the pandemic, he excelled in managing timelines, aligning stakeholders, and supporting the team through various projects of varying complexities.”
Rishab Merwade Former colleague at Infoblox
How I actually work
Four work lanes I keep returning to.
Clean up the record, agree the rule, test the handoff, make the report tell the same story as the process, and only then automate what is worth automating. That's the loop.
Data and reporting
SQL, Python ETL, Power BI, forecasting, the clean numbers behind the dashboards.
AI & automation
Cursor, Claude, local models, prompt libraries, and the judgement to keep it ethical and compliant.
Operations discipline
O2C accuracy, quote cadence, training packs, handovers that stick.
Featured work
Start with these three.
Order-to-cash at Infoblox, how I practice as an AI business analyst, and the MSc thesis. Everything else is supporting evidence.
Featured
CPQ workflow and controls
Infoblox CPQ and order-to-cash
Our White Glove quotes used to vanish into email threads with three approvers and no clean paper trail. I rebuilt the path in Salesforce so reps could move fast without dumping problems on finance and supply.
Outcome 95% White Glove O2C timeline accuracy
Artifacts White Glove CPQ swimlane · CPQ rule decision table
Technical depth / education
AI business analyst practice: automation, models, and governance
How I work as an AI business analyst. I find the business problem first, decide if AI is even the right tool, then build with Cursor and Claude or run a local model when the data can't leave the machine. Same critical thinking I use on CRM and governance work, pointed at automation that has to stay compliant.
Outcome 3 AI-assisted workflows shipped
Artifacts AI fit canvas · AI guardrail checklist
Master's thesis
Master's thesis: breast cancer from histological images
A research prototype (not deployed) that lets a patient, family member, or X-ray tech upload a histology image and get an early read on whether a lump looks malignant or benign. Built as an MSc thesis because waiting on a doctor's appointment for a scan or a second opinion in Europe takes too long.
Evidence 83% CNN validation accuracy
Stack Python · CNN · VGG16
More case studies
Governance and forecast quality
Infoblox CRM governance and forecasting
I standardised CRM governance and KPI definitions across sales, finance, and supply, so planning meetings stopped fighting about whose numbers were right and started feeding real go-to-market calls.
Outcome 60K+ accounts and SKUs under audit scope
Artifacts CRM governance data flow · Data-quality control matrix
Account data quality engine
Infoblox account validation and enrichment
I owned the Greenfield, POC, and enrichment intake, the front door into CRM, as the data steward for incoming accounts. The job was filtering out weak account data before it could break quoting and planning downstream.
Outcome 4 intake tracks owned: Greenfield, POC, enrichment, IC
Artifacts Account intake map · Source-confidence checklist
Production anomaly analytics
Truweight production analytics
I built the anomaly and segmentation logic in production that separated genuine traffic risk from normal campaign noise, so the ops team could act on something real.
Outcome ~15% drop in fraud-related campaign disruption
Artifacts Anomaly data flow · Threshold decision table
Technical depth / education
Technical depth / education
DCU web platform (Agile delivery lead)
I led a seven-person DCU build for a oneM2M IoT dashboard: backlog, sprints, code reviews, release checks, and a working Node/Express platform that turned live sensor containers into Highcharts views.
Evidence 7 person Agile delivery team
Role fit IoT web platform delivery
Technical depth / education
ECG RR-interval alert (edge to cloud)
An EE445 group project. Embedded C++ pipeline on an MSP432P401R doing real-time single-lead ECG analysis with Pan-Tompkins QRS detection, pushing MQTT alerts into ThingsBoard Cloud when the RR interval drops below 0.6 seconds.
Evidence ~85% RR-alert detection accuracy (project setup)
Role fit Embedded systems project
Technical depth / education
BodyBlitz gym booking web product
A short DCU web-application build. Static gym site (BodyBlitz) with home, services, classes, schedule, pricing, and contact sections. Animated landing, responsive nav, mobile-first layout.
Evidence UI flow front-end booking flow shipped
Role fit Web application
Technical depth / education
Mars surface image classification (CNN features + K-Means)
DCU coursework on the NASA Mars Surface Image Dataset (6,691 labelled Curiosity rover images across 25 categories). EfficientNetB0 for feature extraction, PCA for dimensionality reduction, K-Means for unsupervised clustering, with a silhouette score of around 0.12 to 0.15.
Evidence 6.7K NASA Curiosity images clustered
Role fit Computer vision / clustering
Technical depth / education
Block ciphers implemented from scratch
EE5001 Applied Cryptography coursework. PRESENT-80 (lightweight, ISO/IEC 29192-2, designed for IoT-class hardware) and AES-128 (FIPS 197) implemented from scratch in Python, with test vectors. The point was to see the substitution-permutation networks and key schedules end-to-end, not to ship production crypto.
Evidence 2 ciphers implemented
Role fit Security lab
Operations & earlier commercial work
Experience
My BA career, with the Ireland chapter explained.
The main thread is business analysis, CRM ops, data quality, and reporting. After Infoblox I moved to Ireland for the MSc. The Dublin ops roles after that are on the timeline because they belong there, not as a sales pitch in disguise.
quotes, approvals, validation rules, reports, dashboards
account and SKU records I had in active audit scope
automation scouting, local models, ethical guardrails
BRDs, PRDs, stories, acceptance criteria, training notes
BA, CRM, and data work
Freelance AI Trainer / Evaluator
Outlier
- Score AI responses against task rubrics for reasoning, instruction-following, and factual accuracy.
- Write the kind of feedback that's specific enough to act on: what's wrong, where, and how to fix it.
- Bring the Python, data, and analytical habits from my BA and MSc years into the review work.
- Contract work alongside the job search. The rubric and reasoning discipline maps directly to requirements work and UAT.
Salesforce Business Analyst / Technical Business Analyst
Infoblox
- Owned Salesforce CPQ, reports, and dashboards for the global sales op, with Sales, Finance, and Supply all running off the same configuration as requirements kept shifting.
- Reviewed 200+ CPQ quotes a day against a 98% accuracy bar. The pricing fixes I pushed in cut quote errors by about 10% and shaved roughly 25% off issue resolution with sales and partner teams.
- Wrote SQL, Python, and Power BI so the KPI views Sales and Supply argued over actually came from the same place.
- Authored the PRDs, BRDs, KPI definitions, and training docs that forced one definition per metric across Sales Ops, Finance, and Supply, so leadership reviews stopped re-litigating the same numbers.
Data Analyst
Truweight Wellness
- Documented the production data flows, failure modes, and edge cases that kept biting us, sitting next to the engineers instead of throwing requirements over the wall.
- Trained and tuned anomaly-detection models (precision-recall weighted) that cut fraud-style disruption in the marketing pipelines by about 15% in the programme on my résumé.
- Automated customer segmentation for support triage; agents got faster response times and a calmer queue.
Executive Analyst
Sify Technologies Limited
- Lifted sales-planning accuracy by 15-20% through tighter invoice handling, CRM audits, and steady nagging of the right internal teams.
- Tuned Salesforce for the global sales op, roughly 20% more efficient day-to-day while offers kept changing under us.
- Built pipeline visibility packs for segment heads and CIO reviews; the weekly cadences stopped being full of surprises.
- Resolved 85%+ of client queries inside SLA by owning the post-sales follow-ups and upgrade conversations.
Dublin ops roles after the move — transferable skills
Freelance, volunteer, and self-directed study
Career transition before MSc relocation
Corporate Security Officer
Manguard Plus
Retail Security Officer
OCS
Retail Assistant
Eurospar
Certifications
Formal coursework and credentials.
- UNext For Enterprise Analytics with Excel Issued Aug 2017 Credential ID · JRAWE2000844W4
- UNext For Enterprise Data science with Python Issued Dec 2017 Credential ID · JRDSP2001344A5
- UNext For Enterprise Visual Basic for Analytics Issued Jun 2019 Credential ID · JRVBA2007784X1
- UNext For Enterprise Data science with R Issued May 2019 Credential ID · JRDSR2007210Y0
My toolkit
Tools I use to ship the work.
The stack behind the case studies: requirements, controls, dashboards, UAT, governed AI automation, and the handoff docs that keep work from coming back.
CRM & systems
Salesforce CPQ, Sales Cloud, approvals, validation rules, reports, dashboards, flows.
Requirements that admins, IT, sales, and finance can actually test.
Data & reporting
SQL, Python ETL, Power BI, Tableau, Excel, KPI definitions, migration support.
Dashboards with the source logic written down, so nobody has to fight over whose number is right.
BA delivery
BRDs, PRDs, user stories, acceptance criteria, process maps, training docs.
A visible path from messy stakeholder language to something buildable and testable.
Operations control
Order-to-cash controls, account hygiene, quote review, handoffs, SLA follow-through.
Cleaner execution when sales, finance, supply, service, and reporting are all reading off the same record.
AI & automation
Cursor, Claude, prompt libraries, local LLMs, process discovery, automation fit checks.
Repeatable workflows with human review gates, not another pilot that drifts on the first reuse.
Full tool list
CRM & Salesforce
Business analysis
Data & analytics
Delivery
AI & automation
Languages
Education and technical depth
How my DCU work supports the BA story.
My MSc at DCU was in IoT systems. The proof lives in the thesis, the capstone builds, and the coursework, not a long list of modules.
CNN validation accuracy in my MSc thesis
embedded, signal processing, edge-to-cloud coursework
DCU web platform team I led to a live AWS EC2 release
Dublin City University
Master's in Electronic and Computer Technology (Internet of Things)
September 2023 - August 2024 , Dublin
Sai Vidya Institute of Technology, Bengaluru
Bachelor of Engineering, Electrical and Electronics Engineering
2012 - 2016
Kendriya Vidyalaya
Xth and XIIth, Computer Science
2000 - 2012Contact
If the role sits between users, systems, and messy data, I'm probably worth a call.
Best fit: Technical BA, AI Business Analyst, Salesforce/CRM BA, RevOps, Data/Reporting, or Ops Analyst roles. Dublin, hybrid, or remote.
Email is the fastest way to reach me. Phone or WhatsApp work too if you'd rather talk it through.
- Based in Dublin. Happy with hybrid, remote, or relocation for the right role.
- Stamp 1G with full working rights in Ireland.
- Strongest evidence: CPQ/O2C controls, CRM governance, reporting, UAT, and governed AI automation.
Sharing this with someone? Here's the short version, ready to forward.
Email (fastest) Subbu.tripathi.dcu@gmail.com Phone / WhatsApp +353 89 278 3756 LinkedIn Recommendations, role history, easy reply Résumé PDF The portfolio version CRM start here Infoblox CPQ case study, three minutes AI start here AI BA practice case study, three minutes Dublin, County Dublin, Ireland