Data Science Teaching Assistant (Technology Fellowship)

Start Date: September 2024
Employment Type: This is a part-time, temporary, hybrid position
Dates: September 2024 - September 2025
Location: Stamford, CT
Reports to: Data Science Instructor (Technology Fellowship)

General Overview:
The Knowledge House’s mission is to empower and sustain a talent pipeline of technologists, entrepreneurs, and digital leaders, who will lift their communities out of poverty.

The Knowledge House (TKH) approach is to (1) close gaps in the education-to-employment pipeline in underserved communities in the Bronx NY, Newark NJ, Atlanta GA, and Los Angeles CA, neighborhoods by teaching youth and young adults the skills needed to launch careers or ventures in technology, and (2) support links between local youth, tech innovation, and business development that bring positive community impact.

Headquartered in the South Bronx, TKH has served more than 2,250 students since 2014. Current core programs include our Innovation Fellowship focused on software engineering, cybersecurity, and digital design for adult job trainees, and our Karim Kharbouch Coding Fellowship for high school students learning computational thinking and web design.

TKH team members value the opportunity to: apply their skills while giving back to low-income youth and other underrepresented communities; lead innovation in the emerging tech movement in the Bronx, Newark, Atlanta, and Los Angeles; and join a scaling nonprofit where every team member is expected to contribute to strategy, create solutions and helps shape improve organizational culture.

Role Overview
Reporting to the Data Science Instructor (Technology Fellowship), the Data Science Teaching Assistant (Technology Fellowship) will be primarily responsible for partnering with the Data Science Instructor to teach a Data Science Course to 25 adult learners in Stamford, CT. They will be a part of a four person program team managing a learning community through a workforce development fellowship preparing adult learners for jobs in Data Science.
Assisting Instruction and Course Delivery (60%)

• Assist in delivering remote technical curricula Monday and Tuesday during the hours of 5:30 pm-9:30 pm ET November 2024 - August 2025.
• Assist in delivering in-person technical lab support Thursday evenings 5:30 pm-8:30 pm ET November 2024 - August 2025.
• Assist in all classroom management tasks, instruction, and implementation of both guided and unguided labs via Zoom and in-person.
• Manage a calendar/booking system for student office hours, 4 hours a week or as needed via email, phone, web conferencing, and/or in-person tutoring and meetings.
• Review Student Weekly Feedback and provide insight on areas that need to be either reimagined or where students need additional support

Student Support & Evaluation (30%)

• Grade student assignments, labs, and assessments
• Meeting weekly deadlines and updating GPAs before the new week
• Compile all student attendance, incident reports, lab submission rates and grades, weekly assignment submission rates, and grades, and project deliverable submission rates and grades
• Facilitate weekly review session/Q&A with class
• Support students who have entered the pre-training program by monitoring and answering questions via Slack and occasionally providing 1-1 help sessions via web conferencing and/or in-person
• Attend weekly Technology Fellowship team meetings

Curriculum Tasks (10%)

• Support the development of unit plans, lesson plans, and presentation slides, to be prepared for class at least 4 weeks in advance
• Support in creating and maintaining instructional materials including lectures, readings, assignments, exams, labs, projects, etc. for use during in-person and/or virtual settings
• Assist the recruitment and student success team with vetting applicant's baseline technical knowledge to inform the selection needed

Schedule Requirements
Candidates must be available for the specific weekly events described below:

• Weekly class times (Technology Fellowship), October - August (required):
  • Monday and Wednesday 5:30-9:30 pm EST virtually;
  • Thursday 5:30-8:30 pm EST in person at the Synchrony Skills Academy
• Weekly department meeting: Thursdays 4:00-5:00 pm EST (in-person strongly preferred)
• Office hours with fellows: Friday & weekend (time of day is flexible)

The remaining weekly hours are flexible.

Qualifications

• Degree in Computer Science or related field and/or Bootcamp completion a plus
• Proficient in Python3 Programming, Git, and Basic Bash Commands
• Previous experience working in classroom or informal learning environments (virtual or in-person) strongly preferred
• Previous experience working with youth or young adults preferred

Skills & Approach to Work

• Experience with Jupyter Notebooks
• Experience with SQL, Flask/Django, Numpy, Scipy, and Pandas is a major plus
• Familiarity working with API’s to retrieve JSON data
• Familiarity with HTML, CSS, beginner JavaScript, UX/UI, wireframing, web design, graphic design, computational thinking
• Familiarity working with JSON data
• Familiarity with statistical and other mathematical concepts (regression analysis, linear algebra concepts)
• Skilled at problem-solving and algorithmic thinking
• Excellent time management
• Experience using Learning Management Systems (Classrooms, Attendance, Grades, etc..)
• Computer proficiency, including MS Word, Excel, PowerPoint, Google Drive, Google Suite, Google Classroom and other Learning Management Systems
• Teamwork, including actively reaching out to colleagues to support or consult on projects and maintaining a collaborative work environment
• Commitment to contributing to positive organizational culture and core values.
• A passion and love for our students and their genius. A tenacious desire to smash all barriers in the way of our students accessing rewarding, high-paying careers in technology.

Compensation
$27.50 hour for 25 hours per week

It is the policy of The Knowledge House, Inc. to promote and provide equal employment opportunity without discrimination based on age, race, creed, color, national origin, gender, sexual orientation, disability, marital status, veteran status, genetic predisposition, or carrier status.