by oboechick on May 15, 2018

Nicholle James

San Francisco Bay Area, CA

[email protected]

Data Analyst

Effective communicator, spoke about coding education at 3 conferences on 2 continents. My background gives me a unique outlook as I use my experience teaching Mathematics to teach programming. I use Python and SQL to clean and analyze data and HTML and CSS for emails and my website (which is still being created).

Technologies and Skills


Python, SQL, HTML, CSS


Scikit learn, Pandas

Data Visualization:

Seaborn, Matplotlib, Tableau

Data Collection:

Database Management:

Tableau, Google Analytics

SQLite, MySQL, PostgreSQL


Regularization with Lasso, Ridge, ElasticNet, Linear / Logistic Regression, KNN, Decision Trees, Model evaluation with ROC curve, Cross-validation, Grid-search, Random Forest

Professional Experience

GIRLS WHO CODE, San Ramon, CA 2017


Lead instruction and effectively maintained an engaging and accessible classroom environment for a highly diverse group of 20 high school girls. Managed and assessed students’ progress in and proficiency of hard and soft computer science skills (includes administering program evaluations to assess student’s understanding). Managed 2 Teaching Assistants (TAs) who served as support in classroom management, lesson delivery, logistical tasks, equipment managers, etc. Acted as a the on-site representative of Girls Who Code, including serving as host to executive level guests in the classroom and on field trips, thereby supporting the growth and development of Girls Who Code relationships with important partners. Effectively addressed students’ challenges and questions, so as to ensure that all students are engaged and actively learning course material. Communicated regularly and effectively with all Girls Who Code staff to guide the delivery and flow of talks, activities, and field trips to ensure maximum understanding and intake of material for students. Counsel students on professional and personal levels, as needed or requested, with maturity and appropriate discretion. Interfaced with student families as needed.


Consultant (Oboe Instructor)

Oboe instructor for the Hopkins Advanced Elementary Band. I teach the students playing the oboe techniques to improve scales, group music, and audition music.

WAGEWORKS INC., San Mateo, CA 2017

Email Communications Specialist

Reorganized the electronic filing system in Eloqua to match other filing systems to make it easier to find past email campaigns. Created MSRs in Salesforce to help the company keep track of work done for customers for billing purposes. Created a email campaigns in Eloqua to keep customers informed about their account(s) using merge fields to provide personalization (ie first/last names of recipient, balance of accounts, and dates). Created reports using Eloqua, Salesforce, Google Analytics, and Tableau to help show customers strategies that could be used to have better open and  clickthrough rates.

GENERAL ASSEMBLY, San Francisco, CA 2016

Data Science Immersive Student

This is a course to teach data science. In the course I used my background in Mathematics education to analyze reports and present them. I learned about how to use coding to analyze larger datasets, that would take weeks, months, or years to analyze by hand, using the methods listed above.

  • Capstone Project
    • Collected and cleaned data and created visuals to explain the results of student absences and lateness.
  • Weekly assignments
    • Analyzed provided data using Linear and Logistic Regression, regularization of the data to remove outliers, KNN, Decision Trees, Model evaluation with ROC curves, Cross Validation, and/or Grid Search and finishing by creating a presentation to show results of the analysis for the purpose of showing I understood the processes and how to read the results



Filled in for paraprofessionals throughout the district as needed until a full-time position opened. Provided stability and assistance for special needs students and worked with the rest of the class as needed.


Teaching Assistant

Collected and analyzed data on student performance to identify gap areas in knowledge and created new lesson plans.


Teaching Assistant

Ran a section of 25-40 students after lectures on Calculus I for non science majors to answer questions, graded homework, midterms, and finals.

Community Organizer

Organization Title Responsibility Years
PyLadies Organizer Organize an event, find mentors for beginner group 2017- present
BayBridgePython Co-Organizer Organize meet-ups 2017-present
DjangoConUS 2017 Co-Chair of Sprints Organize and help run sprints 2017
DjangoConUS 2018 Co-Chair Organize conference, run organizer meetings 2018


DjangoCon EU 2016 — “5 Ways to Improve Your Beginner Workshop”

DjangoCon US 2016 — “People are coming to my beginning workshop, now what?”

PyDx 2016 — “People are coming to my beginning workshop, now what?”


Artificial Intelligence: Implications for business strategy program, MIT Sloan & MIT CSAIL, Online - 2018

Data Science Immersive Program, General Assembly, San Francisco, CA, 2016

Bachelor of Science (BS), Mathematics with an Emphasis on Education, Music minor California State University East Bay, Hayward, CA, 2016

Completed 300+ credits for BS in Mathematics prior to transferring, University of California Santa Cruz, Santa Cruz, CA, 2011

My Capstone for the Data Science Immersive at General Assembly

by oboechick on October 14, 2016

I started my capstone project by looking for some way to look at the last reports from Trends in International Mathematics and Science Study (TIMSS). This is a group that looks at the way that math is taught worldwide and creates studies to see the best way to teach math so that the students remember it years after they've stopped going to school. TIMSS does this for Science as well but I am less familiar with that branch of the group.

While I was looking for this data I read an article that summarized results from the Organisation for Economic Co‑operation and Development Programme for International Student Assessment (OECD PISA). I discovered that this was one of the umbrellas under which TIMSS published it results. So I dove in and collected the data.

PISA is a group that gives assessments to students ages 15 years 3 months to 16 years 2 months from about 70 different countries. The assessments determine how literate the students are in math, science, language, and finances (starting in 2012). This assessment is given every 3 years starting in 2000. I was able to collect the survey scores from the 2012 assessments.

This data came in the form of over 300 different excel spreadsheets about 250 of them had more than one sheet in the file. I decided that I would start by importing all of the spreadsheets into pandas dataframes and clean all of them with one function. I then followed these steps.

  1. Pulled all of the excel files into pandas dataframe
  2. Left out first row because it was irrelevant
  3. Combined 2nd and 3rd rows to make the headers more descriptive and understandable
  4. Wanted to merge all dataframes together using country column as the index but had the problem of how do I know which question goes with which header?
  5. Added question ID and sheet name to the beginning of every header
  6. Merged all the data
  7. Got dataframe with 65 rows and 4,095 columns
  8. Attempted to use logistic regression.
    1. Used the countries as target y.
    2. Used headers that had words “none”, “once”, “twice”, “four”, and “five” as my  X features.
    3. I got 1,194 columns in my X and I could not get this model to work

There were many problems with the way that I went about this. Apparently not all my headers got cleaned, half of the columns in my features list were click logs not assessment results, and I had click logs and survey results all in the one dataframe.

## What did I learn from this? 

Find a dictionary of the data or create one before you try to analyze it and take your time familiarizing yourself with the data. In the end it will take less time if you don't have to go back and correct things after you have done all the hard work.