Annual report · 2026 editionOpen to new roles

The number nobody trusts is where I start.

I'm Ashish Bangla, Principal Associate in Data & Analytics in Columbus, Ohio. For 10+ years I've turned messy financial, customer and operational data into decisions. I learn how a business works, find the metric people argue about, and rebuild it so finance, operations and leadership read the same number.

10+years in analytics

7domains learned from scratch

8,000+agents measured, to the second

50→7Tableau views consolidated into dashboards

30→10sdashboard load time

1,000+users in weekly sessions

Ten years, seven domains, one habit

Exhibit 01 · Career

Swipe sideways to see the whole timeline →

Discover bars darken with seniority. Hover any bar for the details.

Letter to the reader

“Data work is mostly a negotiation over definitions, not a technical exercise.”

Observe

Sit with the people doing the work before touching the data.

Question

When teams disagree on a number, look for the definition underneath.

Define

Rebuild the metric once, certify it, then make it fast.

Exhibit 02 · Card & bank fraud

One recovery number, not three.

Fraud recovery was counted as disputed balance by fraud date. Misapplied transactions slipped in, and ops, risk and finance each reported a different total.

I rebuilt it at transaction level, by posting month, so every team adds up the same pieces.

recovery = chargeback + rebill − repost + reversal ~~· by posting month~~

OutcomeOne source of truth for finance, operations and leadership.

Illustrative units

Values are illustrative. The calculation is the one that shipped.

Exhibit 03 · People analytics

Flag fewer agents, and the right ones.

The old score was active minutes over paid minutes, against an 80% target. When Desktop Process Analytics failed to capture time, the agent took the hit, and disputes piled up.

I flipped it to track non-active time, and excluded intervals the system never recorded.

OutcomeA productivity measure 8,000+ agents and their managers could accept.

Each square = 80 agents · illustrative shares

22%

of agents flagged

One agent, one 8 hour shift

Exhibit 04 · Workforce analytics

A shift, second by second.

I analyzed Cisco dialer events at one-second grain to build occupancy, utilization, schedule adherence, sign-in duration and paid minutes for 8,000+ agents.

The dial is one shift, 8:00 to 16:30, all 30,600 seconds. Pick a metric to see exactly which seconds it counts.

One example shift

Inner ring is the schedule. The outer ticks mark seconds out of adherence.

Shift generated for illustration. Metric definitions are the ones I built.

Exhibit 05 · Performance management

Weighting a fair ranking.

Ranking agents on one metric rewards whoever games that metric. In OnePM I combined handle time, quality, cases per hour and NPS, each normalized against peers, into one weighted score.

Drag the weights. The left column is the single-metric ranking; the right column re-ranks live.

OutcomeEvery agent ranked on the same yardstick, against peers.

Rank change, 8 agents

Example agents and placeholder weights.

Exhibit 06 · Recovery operations

How fast new hires ramp.

I tracked every new-hire class week by week against the tenured-agent median, and measured speed to proficiency: how many weeks each class took to reach it.

Recovery and Enterprise Strategy leaders used it to compare ramp strategies and staffing plans.

OutcomeTraining and staffing decisions based on how fast each class ramped.

Proficiency vs tenured median, by classIllustrative curves

Hover a panel to read any week. Panels are sorted fastest first.

Exhibit 07 · Data architecture

Teradata to Snowflake, in three tiers.

I designed a three-tier architecture and led the migration from Teradata to Snowflake. Raw data lands as is, gets cleaned by domain, then graduates into a certified semantic layer that every dashboard reads from.

Hover a domain to trace its path.

raw → domain-cleaned → certified semantic layer

Data flowBand widths illustrative

Exhibit 08 · Business intelligence

Fewer dashboards, faster answers.

I consolidated 50+ Tableau views into fewer than 7 dashboards, cut load time from 30 seconds to under 10, and ran weekly sessions with 1,000+ enterprise users so the dashboards actually got used.

I also owned Tableau Server as site administrator, including groups, permissions and the Okta sign-in rollout, and built the Money Drop Report that tracks billions recovered on charged-off accounts.

Grouping illustrative

Load time, seconds

Before

30.0 s

After

<10 s

0102030

Exhibit 09 · Toolkit

Where each tool came from.

Every move added to the kit. Each dot is a tool I used at that stop, so you can see the range grow.

Experience.

Every stop meant a new industry. What carried over was the habit of asking one more question than the brief.

Nov 2017 to present

Discover Financial Services

Now part of Capital One · Columbus, OH

Sr Data Analyst · 2017BI Specialist · 2019Lead Data Science Analyst · 2021Principal Associate · 2026

Fraud recovery metric, the Money Drop Report, Cisco dialer productivity for 8,000+ agents, OnePM ranking, new-hire proficiency, NPS with the CX team, the Teradata to Snowflake migration, Tableau Server administration, and leading and hiring a team of four. Joined in 2017 through Kforce.

Jan to Oct 2019

Cardinal Health

Business Intelligence Developer · Fuse

Drug pricing intelligence comparing ASP and reimbursement across Medicare, Medicaid and commercial payers. Advanced Practice Analytics dashboards on inventory, margins and reimbursement, built with PHI and HIPAA in mind.

Mar to Aug 2017

Bank of America

Data Analyst / Developer · Dallas

Enterprise Independent Testing of risk controls. Aligned data filters with test designers and tuned slow T-SQL with SQL Server Profiler, indexing and partitioning.

May 2016 to Mar 2017

Niftek / Trinity Technosoft

Analyst · Dallas

Requirements for reference data systems through stakeholder interviews, SQL profiling to catch anomalies, and automated SSRS reporting for pharmacy operations.

Aug to Dec 2015

Northern Illinois University

Graduate Research Assistant · DeKalb

Collected data on how US hospitals use social media and supported research linking that engagement to patient readmission rates.

Summer 2013

Adeptech Systems

Intern

Built an HR tool in Excel and VBA that generated plots from the database, plus an automated résumé extractor. The team's work saved $4,000.

Graduate · 2014 to 2015Master's, Management Information Systems

Northern Illinois University · GPA 3.8

Undergraduate · 2010 to 2014Bachelor's, Information Technology

JNTUH College of Engineering Hyderabad · GPA 3.7

CertifiedTableau Desktop Specialist

Plus SSIS and Tableau training · View badge ↗

Questions recruiters ask.

Straight answers. Pick one.

Off the clock.

The observing doesn't stop at five.

Cricket

Went deep on how IPL player contracts and auctions are priced. Best sports dataset nobody asked me to analyze.

Car trouble

Got rear-ended. Worked out the total-loss threshold before the adjuster called back. Occupational hazard.

Wedding

Ran a three-day family wedding like a program launch. Stakeholders: many. Scope creep: also many.

Roots

Telugu at heart, close to family, fluent in English, Hindi and Telugu. I write my own speeches, and the jokes stay in.

In 2019 my résumé was a Tableau dashboard with logos for tooltips and a lollipop chart of my skills. This report is the same instinct, seven years on.

Open the 2019 viz ↗