TF Data Science Instructor - The Knowledge House

Start Date: February  2025
Employment Type: This is a part-time, temporary position, hybrid
Dates: February 3,  2025 - September 26, 2025 
Location: Stamford, CT
Reports to: Senior Manager of Partner Programs

TKH General Overview
Established in 2014, TKH has provided high-tech training to thousands of students from underserved communities across the country. What began as a humble initiative in the South Bronx has blossomed into a national organization delivering programs in Newark, Atlanta, Los Angeles, New York, and Washington D.C. Our mission is to build a diverse tech workforce by uplifting individuals from the most underestimated and underserved communities. We envision a future where all communities have equal access to employment opportunities in tech across all sectors. The TKH model offers in-demand tech skills training, coupled with comprehensive wraparound services to support each Fellow's journey to career success.

Role Overview:
Reporting to the Senior Manager of Partner Programs, the Data Science Instructor (Partner Programs) will be responsible for leading tasks related to Data Science (with Python) class instruction and fellow support, including teaching, assignment review and grading, curricular development support, and holding office hours with fellows.
The Data Science Instructor (Partner Programs) will be a learner-focused professional with a problem-solving orientation and curious mindset who communicates effectively and possesses the ability to: 

• Establish and maintain a supportive learning environment that prioritizes high accountability and respect for individual learning needs.
• Support learners of diverse backgrounds and perspectives
• Manage a high volume of assignment reviews through superlative time management skills 

Key Areas of Responsibility 

Key responsibilities include but are not limited to the following:

Instruction and Course Delivery 

• Teach a cohort of 25 Data Science fellows, with guidance and content provided by the Lead Data Science Instructor
• Lead 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
• Review student weekly feedback and provide insight on areas that need to be either reimagined or where students need additional support

Student Support & Evaluation 

• Grade student assignments, labs, and assessments 
• Meet weekly grading and lesson plan preparation deadlines
• Provide insight into data related to attendance, incident reports, lab submission rates, and grades, weekly assignment submission rates and grades, and project deliverable submission rates and grades
• Attend weekly program team meetings to discuss support strategies for fellows in your track, and review student attendance reports, grades, and classroom feedback
• Support students and facilitate class sessions during the certification prep period

Curriculum Tasks

• Assist with the creation of unit plans, lesson plans, and presentation slides, to be prepared for class several weeks in advance. Working closely with the Lead Instructor, recommend modifications to the curriculum for fellows as needed based on content retention and course pacing. 
• Support in maintaining instructional materials, including lectures, readings, assignments, exams, labs, projects, etc. for use during in-person and/or virtual settings, creating custom materials as needed for regional instructional needs.

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

• Technology Fellowship class time (February-August)
  • Virtually on  Mondays and Wednesdays from 5:30-9:30 pm EST (required)
  • In-person on Thursdays,  from  5:30-8:30 pm EST (required)
    • Location: Synchrony Skills Academy, Stamford, CT
• Virtual department meeting: Thursdays 2:30-3:30 pm EST (required)
• Virtual office hours with fellows: mix of offerings including Fridays and/or weekend options (the time of day is flexible)

Qualifications:

• 2+ years of professional experience in technology or relevant field is preferred 
• 1+ year experience with classroom management, teaching, or working with young adults is required
• Degree in Computer Science or related field and/or Bootcamp completion is preferred

Skills & Approach to Work

• Proficiency in Python3 Programming, Git, and Basic Bash Commands required
• Experience with Jupyter Notebooks required
• Experience with SQL, Flask/Django, Numpy, Scipy, and Pandas is a major plus 
• Familiarity working with JSON data 
• Familiarity with statistical and other mathematical concepts (regression analysis, linear algebra concepts) 
• Skilled at problem-solving and algorithmic thinking
• Experience with eLearning, computer-enhanced teaching, and blended learning approaches preferred
• Experience working with a Learning Management System, including monitoring attendance, participation, and grading 
• Computer proficiency, including MS Word, Excel, PowerPoint, Google Drive, Google Suite,  Google Classroom and other Learning Management Systems 

• Excellent interpersonal communication and persuasive communication skills, including public speaking abilities 
• Ability to independently produce high-quality work, delegate, problem-solve, and ask for help when needed
• 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.
• 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. 

Compensation and Benefits

• $33/hour for up to 30 hours/week
• Pre-tax commuter benefits

It is the policy of The Knowledge House Fellowship, 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.