Showing all posts in November 2018

In Personal

What I Learned at NYC Uncubed 2018

Author AshleyPosted on 1 Comment
What I Learned at NYC Uncubed 2018

Every year, Uncubed hosts a 1-day conference (NYC Uncubed) featuring a fair to connect people with start-up and tech careers. I attended the event in Brooklyn with data science positions in mind and here’s what I learned.

  • Bring physical copies your resume.

    • Print out a few copies of your resume for the event because HR personnel like to mark it up with notes as they speak to you.
    • You can be as aggressive with this as you want. I saw a lot of people with fancy folders filled to the brim with resumes. I brought 5 copies and that was plenty. The amount you bring should be reflective of how interested you are in the hiring companies announced ahead of the event.

  • Lower your expectations.

    • Don’t expect every single recruiter to blow your mind with the work you’ll be doing. Uncubed talks about how this is ‘New York City’s Top Recruiting Event for Digital Talent’, but the reality is that most companies in attendance weren’t revolutionary. If handling health insurance data floats your boat, this might be the conference for you.
    • Not every company is there to offer technical roles. Only a handful of companies out of the total 44 in attendance had openings in data science.
    • Instead of speaking to you about open roles, some companies will simply tell you to refer to their job boards because they’re not sure what specific openings are available.
    • This event isn’t going to change your life if you’re looking for entry-level positions. People straight up want you to have 3-5 years experience for many of the technical roles.

  • Prepare to be judged.

    • Get ready for: “Have you considered attending a bootcamp?” followed by “Where did you even take these classes?” and “I don’t see how any of this experience is relevant.”
    • Telling recruiters that you’re self-taught can freak them out. Some people are super nice and understanding, while others can’t fathom the possibility that you might be changing careers.

  • You don’t need to stay the whole time.

    • The event has a content session from 10:00 AM-1:00 PM and the employer showcase from 1:00 PM-5:00 PM, followed by a casual networking session.
    • The content sessions are something that’s nice, but not essential. It’s mostly people talking about the work they do for their companies in various positions, including data science, human resources, and marketing.
    • Four hours is a bit excessive for the company showcase. If you’re looking for a role in a specific field, it’s best to give yourself 1 to 2 hours to speak to employers. I was finished visiting the companies with data analyst openings by 3 PM.

It was an educational experience to learn the expectations of recruiters and to attend the content sessions. Honestly, I don’t see myself attending NYC Uncubed again. Instead, I’ll focus on industry-specific talks and networking events as future professional growth opportunities.

In Data Science

Project Overview: FoodPact

Author AshleyPosted on Leave a comment
A fork and knife surround a plate that has earth on it and FoodPact is written below.
Logo for FoodPact program

A few months ago I began a project with my brother to create a calculator for the environmental footprint of food. It’s called FoodPact to merge food and ecological impact. It’s a work in progress and I’m excited to share the code for it.

Data sources to inform the calculator include:

  • Water footprint data for crops from a 2011 study by M.M. Mekonnen and A. Y. Hoekstra.
  • Greenhouse gas emissions data from Business for Social Responsibility (BSR) and Environmental Protection Agency (EPA) documents on transport via boat,  rail, and freight.
  • Food waste data from the United States Department of Agriculture (USDA) Economic Research Service (ERS)
  • Global food import data from the USDA Foreign Agricultural Service’s Global Agricultural Trade System (GATS).
  • Country centroid data from a President and Fellows of Harvard College 2015 data file.
  • US city locations from  SimpleMaps.

We used a Bootstrap Bootswatch for the web application’s layout and Flask as the microframework.

Python packages used in the program include:

  • Pandas to create more refined dataframes for use within the application
  • NumPy for equations
  • geopy for calculating great circle distance between latitudes and longitudes
  • Matplotlib and pyplot for creating graphs

The whole point of the program is to take a user’s location, food product, and the product’s country of origin to generate the estimated distance the food traveled, the approximate amount of carbon dioxide that travel generated, and the water requirements for the product.

Conversions include: cubic metric tons to gallons of water, tons of crops to pounds, and grams of carbon dioxide per kilometer to pounds per mile.

Selected graphics from FoodPact project:

One limitation of the calculator is that the values for carbon dioxide consider either full travel by ship, train, or truck and not a combination of the three methods. Emissions refer to the amount it takes to ship a twenty-foot equivalent (TEU) container full of the food product across the world. The country of origin considers the centroid and not the exact location of food production. Similarly, the list of cities displays the 5 most populated cities in that given state. The only exception is New York, for which I considered New York City close enough in latitude and longitude to account for Brooklyn, Queens, Manhattan, the Bronx, and Staten Island.

The data referenced in the calculator is meant to give a relative idea of the inputs required to generate and transport food products to give perspective to consumers. Ideally, the calculator will encourage conversations about the food system and inspire people to reduce their personal food waste.