Data Dish ~ Come and get it! This is bimonthly newsletter for the Bay Area’s data analytics community. Data Dish serves to provide you with insight as to who we are and what we’re doing at Intuit.

1. Data Dish March/April Edition
Check out Data Dish! This is your bimonthly newsletter for the Bay Area’s data
analytics community. Data Dish serves to provide you with insight as to who we are
and what we’re doing at Intuit.
Each edition includes three useful parts:
1. Our Awesome Leaders – a data analytics leader shares his/her journey to
Intuit and current projects
2. Big Things in Data – a peek into what’s going on inside Intuit’s data walls
3. Hot Careers to pursue – a snapshot of what positions we’re looking to fill
We’re excited to get you in the loop of our world and in turn, share it with your
friends. We encourage reader engagement – tell us what you think and what you’d
like to know. Happy reading!
Spotlight — Our Awesome Leaders

2. Russ Zaliznyak
Sr. Technical Data Analyst
We recently sat down with Russ
Zaliznyak, Senior Technical Data Analyst,
in Intuit’s Small Business Group. We
wanted to understand his journey joining
Intuit, leaving and coming back again.
Q: Let’s start from the beginning. Where did
you grow up? What was that like?
A: I was born in the Ukraine and moved to San
Jose when I was 4 years old. My family didn’t
realize then that the Bay Area would be the hub
of technology,so I was very lucky. My parents
both worked very hard to make a life for us
here. We were on welfare but got the support
we needed to live from the government and our
local community center. Education was always
important. I studied finance at Santa Clara
University where my Capital Markets course
professorsaid I had to double down on my
math and science skills to further my career. I
ended up earning a second bachelor’s and a
master’s degree in mathematics.
Q: What’s your current position today?
A: I’m a Senior Business Data Analyst.I make
sure people have the numbers they need to do
their business and build out infrastructure to
make it is easy to build reports.I do A/B test
designs and build a lot of dashboards tools.
We’re getting a lot more into predictive
analytics, which I’m really excited about.
We’re trying to get to the point where we can
take actions based on early indicators. For
example, we might send out advertisements
based on usage data.
Q: How did you end up at Intuit?
A: Near graduation I heard about the company
Homestead. They liked me and hired me as a
Junior Analyst.What I didn’t know when I
started was they had just been purchased by
Intuit. I thought going into my job that because
I was successfulin schoolI’d be successfulat
work. That wasn’t the case. It took a lot of
mentorship and support from a senior manager
for me to be successful.I was learning the
business and howto transfer my university
skills into the business.Eventually I became
the go-to analyst when my manager left.
Q: Why did you leave Intuit and return a few
years later?
A: Around my 3-year year mark at Intuit I felt
like it was time to shift gears and explore other

3. opportunities both inside and outside Intuit. I
decided to go to Disney and try that world. I
simultaneously pursued my master’s degree.
After two plus years I was experiencing a lot of
life changes – graduating with my masters and
becoming a husband and father. It was the
appropriate time to reassess my career. I always
knew Intuit provided a good work-life balance
and great benefits.I had to start thinking as a
family. Not only did I want to have the most
fun and have the best career, I knew there were
so many talented people from whom I could
learn, and many other people with families. I
felt it was the right move to come back to
Intuit
I knew at Intuit there would be good work and
abundant resources devoted to that work.
That’s what kept my eyes away from startups.I
didn’t want to go somewhere where there was
risk that the funds would be redirected from my
work or get cut off. When I left Intuit, I thought
they were behind the curve in data analytics
and they weren’t serious about catching up.
When I came back in 2011 I made a 180 degree
turnaround in my prospective.I realized we
were serious about investing in great data. I’m
seeing the benefits of the work we’re
producing. We are truly becoming a data leader
in technology based on the work we’ve done
and the people we’re hiring. I feel more
optimistic than ever before about my career at
Intuit and the mentorship I can get here with
the talent we’re hiring. I’m excited that I'm
surrounded by people who have a lot of skills,
many of the skills I just don’t have. Each time I
collaborate with someone I learn something
new that I can add to my skillset. That makes
me increasingly well-rounded and gives me
more potential.
Q: What advice would you give someone going
into a data analytics position for the first time?
A: Try to become a Renaissance woman or
man and diversify yourskills as much as
possible.It’s not just about being a really good
coder, statistics person or presenter.Develop as
many professional skills as you can, whether
you think they’re applicable to data analytics or
not.
Big Things About Data

4. Big Data for the Little Guy
Embedded Experimentation at Intuit Yields a SuccessfulData Product
Intuit Inc., like a growing number of innovative companies these days,is trying to provide value to its
customers from the vast amount of data it stewards on their behalf. Intuit is entrusted with the collective
data of 45 million customers — a unique pool of data that covers the financial spectrum, ranging from
individual purchase history to business inventories.The company has a culture of experimentation, and its
founder, Scott Cook, has encouraged employees to experiment (rather than listen to their bosses).
But the company has found that fully bottom-up experimentation is not enough to create great new data
products and services. It learned that it also needs professional data scientists to surface and implement
business opportunities based on data and analytics, and it has hired or acquired a substantialnumber of
them. There are still not enough data scientists to serve everywhere in the company, however, so the
central Data Science and Analytics organization did its own experiment: it requested business proposals
from product teams competing to have an embedded data scientist for 3 to 6 months.
In one early case, the experiment was successful.One of the winning product teams was QuickBooks
Financing (QBF), a nascent “two pizza” team whose mission was to leverage the power of QuickBooks
data to simplify the loan application process and match qualified small businesses with lenders. QBF got
an offering off the ground,in part with help from its assigned data scientist,Diane Chang.
Intuit’s experience suggests not only the virtues of experimentation and the importance of data products,
but also the value of a “forward deployment” / “embedded tourof duty” / “special forces” model for
strategically deploying data scientists.Other companies, including Procter & Gamble have also gotten
great value from the embedded analyst model.
The QBF team knew that many small businesses,especially new ones,have difficulty getting the
financing they need. Analysis revealed that the majority of SMBs (60% of QuickBooks users)sought
financing in the last 2 years, but 70% of those applications were rejected. Credit risk underwriting for
small businesses is often not based on the health of the business,but rather on the personal credit scores
of the principals. Banks also have a bias toward the specific industries that they understand best.
The systemdoesn’t always work well for banks either. They often find it hard to find qualified leads, and
the low approval rates due partly to the focus on personaldata lowers their productivity and their ROI,
particularly for loans under $50,000.
So Intuit’s vision was to deliver one-click funding to all QuickBooks SMBs who needed and deserved it.
Ms. Chan was asked by the QBF team to dive into the data.She initially looked at the historical
QuickBooks data underthe hypothesis that it could directly predict a small company’s default risk.
However, it quickly became clear that Intuit could provide the highest value by carefully matching a small
business to a financing provider based on the historical QuickBooks data of the small business and the
attributes of the financing provider.
Ms. Chang developed a matching process that accesses the small businesses’QuickBooks data, including

5. details like yearly revenue, number of years in business,industry,and so on. The process then compares
these numbers against each lender’s criteria to find the best match. QuickBooks Financing only
recommends applicants to vetted lenders who are likely to approve them, can offer the best terms (in
many cases the banks offer QBF-screened applicants betterrates than if a SMB walked into a branch) and
offer an easy closing process.
Since its debut a year ago, QBF has connected over2,000 small businesses to over$100 million in
funding. Seventy percent of pre-screened applicants are approved,compared with a 70% rejection rate for
the industry.And because applicants complete a single, simple form, those applicants are delighted with
the ease of the experience.
Furthermore, the QuickBooks Financing product team has grown, and has hired its own full-time data
scientist and a couple of data analysts.The success ofthis “data product” in QBF has inspired other
groups within Intuit to look for more, with heavy encouragement from Mr. Cook and Intuit’s management
team. Ms.Chang has moved on to work with other teams and the corporate group,but she and other data
scientists who have been assigned to opportunities like QBF believe that it’s a great way to connect data
science expertise with real business opportunities.
Thomas H. Davenport is a Distinguished Professor at Babson College,a Research Fellow at the Center
for Digital Business, Director of Research at the International Institute for Analytics, and a Senior
Advisor to Deloitte Analytics.
George Roumeliotisis currently a SeniorData Scientist at Intuit, where he leads strategic initiatives to
drive businessgrowth through innovative applications ofdata and analytics.He also leads company-wide
programs to develop and mentor early career data scientists and data analysts.Prior to Intuit, he has
extensive experience leading the design and implementation of data-driven business solutions in fields
ranging from computational advertising to just-in-time supply chain planning.And,in a previous life, he
was an astrophysicist studying magnetic and plasma phenomena on the Sun.
Article source: CIO Journal: http://mobile.blogs.wsj.com/cio/2015/01/21/embedded-experimentation-at-
intuit-yields-a-successful-data-product/.
Hot Jobs
 Business Analyst
 Senior Data Engineering Manager
 Data Scientist
 Social Analytics Leader,US and Global

6. Data
 Check out more data opportunities here
*First Name
*Last Name
*Email