Overview
Work History
Education
Skills
Additional Information
Timeline
Writings
Generic
Salil Waknis

Salil Waknis

Student
State College,PA

Overview

3
3
years of professional experience

Work History

Customer Success and Statistics Intern

Plobal Apps
Pune, Maharashtra
06.2023 - 08.2023
  • Collaborated with the Head of Customer Success to research and analyze over 30 client companies' key performance indicators, benchmarking against industry standards to predict trends for Q4 2023 and the first two quarters of 2024
  • Generated predictive models for 3 upcoming quarters, using online trend analysis and developed a raw prediction column
  • Utilized Excel and Stata to build a logit regression model, improving forecast accuracy by 12%
  • Shadowed 15+ client calls to understand their key metrics and business objectives, incorporating 5+ essential variables into the predictive models for more tailored quarterly forecasting.

Customer Service Intern

Apace Apparel
Pune, Maharashtra
05.2022 - 08.2022
  • Collaborated with the marketing department to develop promotional plans for 5+ new product launches, ensuring timely release and effective advertising strategies.)
  • Conducted 20+ interviews with cyclists and triathletes to identify key apparel features valued by athletes, using feedback to create targeted marketing plans
  • Assisted with inventory management, overseeing 200+ products, and handled customer service tasks, including answering 50+ customer calls, emails, and inquiries weekly
  • Played a key role in improving customer satisfaction by reducing action time for inquiries by 15% through efficient coordination of customer service calls and emails., Developed marketing plans for 5+ product launches
  • Conducted customer interviews and managed inquiries to reduce response times by 15%
  • Projects
  • IPL Auction Predictor (2023)
  • Achieved 70% prediction accuracy in forecasting cricket player auction outcomes using Stata
  • Engineered a dataset of 200+ players and incorporated statistical interactions for improved model fit.

Indian Premier League Auction Predictor State College
, Pa
09.2023 - Current
  • Developed a predictive model in Stata to evaluate over 100 T20 cricket players for team auctions, incorporating key performance metrics such as average run rate (6.5-9.5), average wickets per game (0.5-2), and auction prices ranging from $50,000 to $200,000
  • Utilized logit regression analysis to achieve a 70% prediction accuracy in determining the likelihood of a player being purchased based on statistical performance and market value
  • Engineered a dataset of over 200 player observations and purchase outcomes to assess player value and buying decisions
  • Introduced interaction terms to capture the effect of performance metrics relative to auction price, improving model fit with a Pseudo R-squared of 0.21.

Customer Success & Statistics Intern

Plobal Apps
Pune
06.2023 - 08.2023
  • Analyzed 30+ client KPIs to benchmark industry trends and predict quarterly forecasts
  • Developed predictive models using Excel and Stata, improving forecast accuracy by 12%
  • Participated in client calls to integrate customer metrics into tailored solutions.

Education

College - undefined

The Pennsylvania State University, Liberal Arts
2025

Bachelor of Science - Economics

The Pennsylvania State University
May 2025

Skills

  • Skills & Honors
  • Skills:
  • Java, Stata, Excel, Data Analytics, Professional Elocution

Additional Information

  • HONORS, SKILLS & INTERESTS Honors: , Bunton Waller Scholarship, Certificate of Academic Excellence in the department of South Asian Studies (2023 and 2024).
  • Honors: , Bunton Waller Scholarship, Certificate of Academic Excellence (2023, 2024) Application Letter for Data Analyst Intern Position

Timeline

Indian Premier League Auction Predictor State College
09.2023 - Current

Customer Success and Statistics Intern

Plobal Apps
06.2023 - 08.2023

Customer Success & Statistics Intern

Plobal Apps
06.2023 - 08.2023

Customer Service Intern

Apace Apparel
05.2022 - 08.2022

College - undefined

The Pennsylvania State University, Liberal Arts

Bachelor of Science - Economics

The Pennsylvania State University

Writings

The Real-World Economics of Nash Equilibrium:

 A Beautiful Mind’s Inspiration
Watching A Beautiful Mind, the powerful story of mathematician John Nash, brought his
groundbreaking concept of Nash equilibrium to life in a way that resonated deeply. It was
fascinating to see how one mathematical idea could explain so many everyday decisions and
interactions. This sparked my curiosity about how Nash equilibrium operates in the real world,
outside of the theory-laden classrooms of economics.
In essence, Nash equilibrium is the point in a game where no player has anything to gain by
changing only their strategy, assuming everyone else’s strategy stays the same. This idea
applies in numerous practical situations where multiple parties make decisions that impact one
another.
Consider, for example, the dynamics of price competition between companies. In a Nash
equilibrium, each firm settles on a price that maximizes its profits given the pricing strategies of
its competitors. If one firm decides to lower its price, it risks setting off a price war, lowering
profits across the board. The equilibrium prevents this, creating a stable market price that
benefits all players.
Another relatable scenario that I immediately thought about is traffic flow. Each driver selects
their route based on what they think others will do, leading to a situation where no one can
reach their destination faster by choosing a different path. This equilibrium explains why
sometimes, despite congestion, changing routes wouldn’t improve commute times.
The application of Nash equilibrium to areas like politics, trade, and even social behavior
reminds us of its pervasive influence in aligning self-interests in a balanced way, even if it’s not
always the most optimal outcome for all involved. Watching A Beautiful Mind didn’t just
introduce me to Nash’s remarkable life but also shed light on the quiet logic underlying complex
systems around us.

The Economics Behind Apple’s Push into Subscription Services
Apple's shift towards subscription services marks a strategic pivot in response to evolving
market demands and shifting consumer behavior. With a saturated smartphone market and
slower growth in hardware sales, Apple’s expansion into services like Apple Music, iCloud,
Apple TV+, and Apple Fitness+ is more than just a diversification, it’s an economic
transformation aimed at stabilizing and growing its revenue streams.
Subscription based models provide Apple with predictable, recurring revenue, insulating it from
the fluctuations of hardware sales cycles. From an economic perspective, these models align
with a strategy that prioritizes customer lifetime value over one-time purchases. Rather than
relying solely on high-priced devices that consumers may upgrade only every few years, Apple
can generate ongoing revenue through monthly fees, deepening its engagement with existing
users while reducing reliance on new device sales.
Furthermore, I've realized that subscriptions create a “lock-in” effect, increasing switching costs
for customers. Once users are embedded in Apple’s ecosystem, backing up data on iCloud,
tracking health stats on Apple Fitness+, enjoying exclusive shows on Apple TV+. It becomes
less convenient and costlier for them to switch to competitors. This network effect not only
encourages loyalty but also enables Apple to gather more data on user preferences, which can
be leveraged to enhance existing services or develop new ones, ultimately leading to increased
average revenue per user.
I also Believe that Apple's services push also represents an important hedge against
competitive pressure and market maturity. With subscription services, Apple taps into stable,
high margin income that can offset the competitive volatility in hardware markets, where
margins are often tighter and competition fierce. For consumers, subscription services offer
flexibility and access without large upfront costs, reflecting an economic shift toward "ownership-
free" consumption patterns.

Salil WaknisStudent