Help & Supportcareers@gravityer.com
Machine Leaning Enthusiast .
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
NYC-Parking-Tickets-An-Exploratory-Analysis
July 30, 2018 – July 30, 2018
Problem Statement Big data analytics allows you to analyse data at scale. It has applications in almost every industry in the world. Let’s consider an unconventional application that you wouldn’t ordinarily encounter. New York City is a thriving metropolis. Just like most other metros that size, one of the biggest problems its citizens face, is parking. The classic combination of a huge number of cars, and a cramped geography is the exact recipe that leads to a huge number of parking tickets. In an attempt to scientifically analyse this phenomenon, the NYC Police Department has collected data for parking tickets. Out of these, the data files from 2014 to 2017 are publicly available on Kaggle. We will try and perform some exploratory analysis on this data. Spark will allow us to analyse the full files at high speeds, as opposed to taking a series of random samples that will approximate the population. For the scope of this analysis, we wish to compare phenomenon related to parking ticke
View ProjectRetail-Giant-Sales-Forecasting
July 30, 2018 – July 30, 2018
“Global Mart” is an online store super giant having worldwide operations. It takes orders and delivers across the globe and deals with all the major product categories - consumer, corporate & home office. Now as a sales/operations manager, you want to finalise the plan for the next 6 months. So, you want to forecast the sales and the demand for the next 6 months, that would help you manage the revenue and inventory accordingly. The store caters to 7 different market segments and in 3 major categories. You want to forecast at this granular level, so you subset your data into 21 (7*3) buckets before analysing these data. But not all of these 21 market buckets are important from the store’s point of view. So you need to find out 2 most profitable (and consistent) segment from these 21 and forecast the sales and demand for these segments.
View ProjectChinese-automobile-pricing-problem
July 30, 2018 – July 30, 2018
A Chinese automobile company Geely Auto aspires to enter the US market by setting up their manufacturing unit there and producing cars locally to give competition to their US and European counterparts. They have contracted an automobile consulting company to understand the factors on which the pricing of a car depends. Specifically, they want to understand the factors affecting the pricing of cars in the American marketing, since those may be very different from the Chinese market. Essentially, the company wants to know: Which variables are significant in predicting the price of a car How well those variables describe the price of a car Based on various market surveys, the consulting firm has gathered a large dataset of different types of cars across the American market.
View ProjectCultural Fit Analysis
The candidate's projects primarily focus on data analysis and machine learning, which aligns with a Data Scientist role. However, the projects are all personal and lack diversity in terms of team collaboration or real-world business impact. The absence of work experience or certifications limits the assessment of cultural fit beyond technical alignment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.