Recent Hunt for a New Job

Over the summer I began looking for new employment opportunities. It has been a good number of years since I last applied for a job and it was interesting to see how quickly some organizations contracted me after my initial application (either with an interview request or a rejection email).

I thought it would be fun to visualize the timing of responses.

#Load job application data
data <- read_xlsx("2021 Job Applications.xlsx")

Dataset Setup

Response times ranged from 1 to 52 days.

I updated the dataset with a few additional variables to associate color and shape in the plot. I censored applications that had no response with a date of 1 day following the last response I received.

#Get the shortest and longest response time. 
data %>% 
  mutate(Diff = Response_Date-Date_Applied) %>% 
  summarise(Shortest_Response = min(Diff, na.rm = T),
            Longest_Response = max(Diff, na.rm = T))
## # A tibble: 1 x 2
##   Shortest_Response Longest_Response
##   <drtn>            <drtn>          
## 1 1 days            52 days
#Censor the NAs in Response_Date (which means no response was received) 
#to the day after the last response 2021-09-24
data$Response_Date[is.na(data$Response_Date)] <- as.Date(max(data$Response_Date, na.rm = TRUE)) + 1

#Get a count of the number of days from first application to last response
max(data$Response_Date) - min(data$Date_Applied)
## Time difference of 69 days
#Add a day counter for each job applied during the 71-day range 
data <- data %>% 
  slice(rep(1:n(), each = 71)) %>% 
  group_by(ID) %>% 
  mutate(Day_Count = 1:71) %>% 
  mutate(First_Apply = min(data$Date_Applied),
         Last_Reply = max(data$Response_Date)) %>% 
  mutate(Day = as.Date(First_Apply) + Day_Count - 1) %>% 
  mutate(Keep = case_when(Day >= as.Date(Date_Applied) & 
                            Day <= as.Date(Response_Date) ~ 1,
    T ~ 0)) %>% 
  filter(Keep == 1) %>% 
  group_by(ID) %>% 
  mutate(Day_Linger = row_number())

#Add a flag for the day the response was received. 
#Those with 9/25 (no responses) are coded as 0

data <- data %>% 
  mutate(Response_Flag = case_when(Day == "2021-09-25" ~ 0,
    Day == as.Date(Response_Date) ~ 1,
    T ~ 0))

Plot

This project is mostly an excuse to try out gganimate. The plot slowly progresses through time, starting at the first day I submitted a job application and stopping the day after the last response was received. When a response is received for an application, a star is noted at the end of the row. This plot does not show the kind of response received (interview request vs. rejection).

The longer the application had been sitting without a response, the lighter the row becomes until it fades out to white.

#
p <- ggplot(data, aes(x= Day_Count, y = ID, group = as.factor(Response_Flag))) +
  geom_point(aes(color = Day_Linger, 
                 shape= as.factor(Response_Flag),
                 size= as.factor(Response_Flag))) +
  labs(title = "Time until Reponse to Job Applications",
       y = "Number of Applications Submitted",
       x = "Days Since I Started Applying")+
  scale_y_continuous(limits = c(0, 50))+
  scale_x_continuous(breaks = c(0,10,20,30,40,50,60,70))+
  scale_shape_manual(values=c(15, 8))+
  scale_size_manual(values=c(2.8,2))+
  scale_colour_gradient(high = "grey100", low = "grey0")+
  theme(
    panel.background = element_blank(),
    panel.grid = element_blank(),
    legend.position = "none",
    plot.title = element_text(hjust = 0.5)
  )

p2 <- p + transition_time(Day_Count)+
  shadow_mark(alpha = 1, size = 2)

animate(p2, fps = 5)

The End

I knew that applying to jobs would be time consuming; however, I forgot how emotionally taxing the process can be. Waiting to hear back from a job you think would be a great fit - but they never respond, getting rejected only one day after you put in an application, getting a request for multiple interviews at the same time and juggling each of them. I am glad I was able to end my job search after 70 days. I am looking forward to spending my free time on basically anything else.