As University. During summer of 2014, when I

As a child, I was always fascinated by mathematics, not because I understood
that subject well, but because I was effortlessly good at it. Back then I
considered myself a math prodigy. Growing up, when I started seeing numbers on
television, I thought mathematics makes more sense when applied in real-time
scenarios. However, it was only later that I realized how numbers can be
misleading if you don’t understand them; how predictions have built in bias; and the word
‘average’ has a lose meaning.

My
interest in statistics became profound when I was in my third year of undergraduate
studies pursing Electronics & Telecommunication Engineering at the
illustrious KIIT University. During summer of 2014, when I was keenly following
the 16th General Elections of India, I observed a shift from
political strategists, who relied on hunches and intuitions, to actuaries and
data scientists, in “electioneering”. After reading through various
articles on how the winning party used a scaled-up model of data-driven
election campaign model used by U.S. President Obama, I realised that the impact
of data-driven decision making is humongous. It was the first time that big data
was being used extensively in the largest democratic exercise of the world to
drive donations, enrol volunteers, and organize resources on the ground from
door knocks and phone calls, to micro-messaging and social media. Keenly
following the event, helped me learn how the use of data and analytics in
untapped areas such as education and agriculture etc. can positively impact the
government. This
encouraged me to join a decision science firm upon graduating.

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When I joined Mu
Sigma in 2015, I was staffed into one of its flagship engagement, to provide
data-driven solutions for the e-commerce division of world’s largest software
maker. My first challenge there
was helping the client curtail mid-purchase drop-offs. Working in a
four-membered team, I carried out several statistical analyses and recommended
few merchandising changes for the store. In our quest to add value, we put in
extra effort to build a demand generation time-series forecasting model that
gauged the dollar-value impact of suggested changes. Even though we missed our
goal by a small margin, the model was well received by the stakeholders and we
were highly appreciated for our efforts. During the project, I learned the
nuances of building an analytical framework bottom-up and technical concepts of
SQL, VBA, and Python. My
stint in the e-commerce vertical intensified my passion and gusto towards
decision sciences.

In 2016, I
joined a new engagement that was providing analytical support to one of world’s
largest research-based biopharmaceutical company. My first major project here
was to help the client optimize sales-force effort allocation across all
products in company’s portfolio. Initially, our team was under a lot of
pressure as the engagement was in its nascent stage and the client was
extremely demanding. However, we thrived under pressure and worked hard to
build a regression model that estimated historical sales response for each
physician segment. To ensure great client experience, we went an extra mile to
implement the outcome of the analysis in Tableau.

In 2017, I was
promoted to a Team-Lead, spearheading various process improvement projects and
handling business development for emerging clients. Currently, I am working on
gauging the impact of drug sampling, the project has helped me gain proficiency
in statistical language R. As a team-lead, my responsibilities include setting
& communicating goals, scope, and timeline for the project, managing
dependencies, identifying roadblocks to delivery, and mentoring new joiners in
the team.

 

My learnings at
Mu Sigma has helped me comprehend the boundless potential of analytics in
various industry. The comprehensive curriculum of the BIDA track at Carnegie
Mellon’s MISM program is tailor-made to equip me with analytical skills and the
necessary knowhow to realize my career objectives. Courses such as ‘Applied
Econometrics’, ‘Advanced Business Analytics’ and ‘Machine Learning for Problem
Solving’ would help me build a muscle in quantitative analysis of
economic phenomena, big data, and machine learning. Experiential
Learning, through ‘Data Analytics Capstone Project ‘and summer internship,
would help me hone my business acumen and analytical capabilities. Given my
diverse experience as an analyst coupled with the enthusiasm for social
services, I see myself not only adhering to the University’s community
standards code but also contributing to the college community by taking up
responsibilities in Grad school.

Armed with a
Master’s degree, I anticipate working for renowned big data consulting firms
known for their strategy experience and analytical expertise such as
Bain , Booz Allen Hamilton Inc etc. to understand
end-to-end business processes. Fast-forwarding ten years, I envision working
with the Indian government, Public-Private Partnership, through my own big data
analytics and decision sciences firm to chart out citizen-centric policies
leveraging big data analytics, enable the citizens to connect with the
government, and contribute towards good governance. Coming from a youthful
nation, which generates huge amount of data in public sector, motivates me to
leverage my skills to help the government achieve efficiencies, combat fraud,
bring transparency, foster economy, and spike productivity and growth. Also, institutionalizing
data-driven decision making for customizing social benefits and subsidies to
every citizen of the country remains a realm largely untouched.

 

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