I am drawn
to the MS in Data Science program at New York University because I believe the
experience will allow me to pursue my mission of improving the lives of nearly
two billion people who do not have access to formal financial services. My long-term career goal is to lead
the Data Analytics function in a global fintech firm and help it leverage
predictive analytics to extend financial services to people without a credit
history.
Immediately after complementing my technical skills gained at FICO with a
robust training in data science AA1 at NYU , I plan to join the data
analytics team in a credit scoring or a fintech company such as Biz2Credit AA2 which will set me perfectly for my
long-term goal. I am keen to help companies integrate the newly available
behavioral and social network data with existing systems and push the boundary
in increasing financial inclusion. Growing up in
North India, I often assisted my mother, a Math teacher, in tutoring children
from disadvantaged backgrounds. This sparked my interest in Math –  I started to devote my free time to the
subject and the more I learnt its secrets, quirks and applications, the more I
became fascinated with it. I realized that my fascination with mathematics is due to the
beauty, complexity and logical structure which become apparent in the process
of solving a problem: what may at first look difficult, and without obvious
point of attack, can be solved through steady work and perseverance.  AA3 I expanded my horizon through numerous Math quizzes and Olympiads,
and topped the nation-wide high school Math exam. After school, while there
were not many friends who wanted to pursue a career in Mathematics, I decided
to follow my interest and pursue a major in Math. Hence, I was thrilled on
being admitted to the graduate Mathematics program at BITS Pilani – one of
India’s top-rated academic institutions.  In BITS Pilani, I enjoyed exploring different avenues besides
academics, such as playing badminton at the university level and coding a
virtual touch screen controlled by hand gestures. However, I realized that my
true calling was Applied Math as I was excited by using math to solve
real-world problems.
For instance, I maximized the empty space in my hostel room by optimizing the
placement of different items such as bed, study table. AA4 I joined the
Mathematics Association and organized interdisciplinary events and talks to
help increase awareness about the different real-world applications of Math. At
the end of my third year, I was thrilled on being selected for a coveted
research internship in Applied Math at University of Toulouse, France. During
the internship, I implemented numerical techniques to reduce time complexity in
computing Green’s function, which could help improve hearing aids and digital
microphones. Back in India, I took up research on “Reliability Prediction of
Machine Repair” as my Master’s thesis. Using an M/M/1/K queue model, I
optimized the reliability of a machine system considering various operational
constraints. These experiences have fostered my desire to solve real-world
problems using a synergy of Math and Computing.  To follow my
interests, I embarked on a career in Data Analytics with FICO upon graduation.
As a part of the Scores and Predictive Analytics Group, I got the chance to
work on innovative big data projects, such as creating a software which extended credit access to ~20 million
people in Philippines by analyzing their mobile phone usage. Along with
ameliorating my skills in Java, Python, Spark and FICO Model Builder, these
projects helped me improve my teamwork and communication skills. My
contribution to the firm was rewarded with the Spot Award in 2016.  I was also selected twice to attend FICO’s
annual event in San Francisco, which provided me with multicultural experience
and expanded my professional network. Recently, I was given the responsibility
of leading a small team to integrate alternative data sources (e-mails, text
messages, etc.) with FICO’s traditional credit scoring engine to make
risk-prediction more accurate.My work experiences in FICO have made me realize how unstructured
information from these alternative data sources could be extremely valuable.
Further, the quantity of such data is growing exponentially due to which
efficient machine learning algorithms will soon be indispensable. In order to
widen my knowledge of regression models and statistical hypothesis AA5 testing, I decided to
pursue an Actuarial Certification course (CT3 module), which has helped me stay
connected with academics. I now wish to further expand my understanding of data
analytics by pursuing
a Masters in Data Science, and make a difference in the industry.Indeed, NYU’s vision
of turning data into insights and transforming the way business, government, science and healthcare
are carried is perfectly in line
with my objectivesAA6 . My discussions with
Abhishek Kadian’16 have convinced me that NYU offers an inspiring environment
to learn. I aspire to
develop a deep understanding of optimization algorithms used in Machine
Learning through the unique Data Science Mathematics and Data Track. I am interested
in the research areas of Prof. Afonso S. Bandeira and Prof. Carlos
Fernandez-Granda and look forward to the opportunity of collaborating and learning with themAA7 . Furthermore, NYU’s strong alumni base would be an unbelievable long-term resource
that I can leverage for guidance and career opportunities. Lastly, NYU’s location in New York, one of the world’s greatest
tech innovation hubs and the most powerful city in finance, would enable me to gain better access to
industry professionals, setting me perfectly for my long-term goal of using
data science to improve lives.AA8