Grader - Machine Learning Career Track (Part-time/Remote)

The Opportunity

We’re expanding our Machine Learning Career Track services to support successful outcomes for our students. Are you passionate about data science, programming, and helping curious data science students master fundamental skills that will lead them to great careers? This position may be for you!

We are looking for a detail-oriented grader to grade projects and exercises that students complete in an online bootcamp course. You will utilize existing materials to assist with grading submissions in a timely manner and provide feedback to students as they proceed through the course. This is a remote, part-time contract role with a flexible schedule, reporting to the Outcomes Program Manager.

Responsibilities:

• Evaluate student machine learning projects. These projects cover a variety of fundamental machine learning skills and concepts with a focus on student acquisition of course content
• Provide written feedback on assignments informed by Springboard’s rubrics and solution sets, feedback will lead to student growth
• Evaluate student projects promptly to give them quick feedback
• Communicate with student’s mentors to resolve questions, provide clarity on their strengths and weakness, and calibrate feedback when necessary
• Escalate at-risk students through appropriate channels and Program Manager
• Graders may need to evaluate presentations for executive, technical, and non-technical audiences (synchronously)

Skills:

• Excellent machine learning technical skills
• Experience in Python Data Science Stack; using python and its standard libraries; building visualizations with Matplotlib and Seaborn;Writing code in Python using PEP 8 Standard
• Data Wrangling: Use Pandas to wrangle and clean data; working with different file formats, from plain text, to CSV, to JSON; relational and non-relational databases; SQL
• Machine Learning: Scikit-learn; ML techniques: linear and logistic regression, trees, and clustering;
• Deploying ML: Experience deploying ML solutions with a cloud service provider (at least one of AWS, GCP or Azure).
• Deep Learning Fundamentals: Familiarity with deep learning, computer vision, natural language processing
• Expertise in Python, libraries like TensorFlow and PyTorch, SQL, cloud ML, etc.
• Inferential Statistics; basics of inferential statistics and parameter estimation; hypothesis testing; correlation and regression; A/B split testing; exploratory data analysis
• Degree in machine learning/AI/data science preferred
• Excellent written communication skills
• Ability to give detailed and actionable feedback
• Ability to strike a balance between maintaining objective grading baseline and allowing subjective considerations
• Ability to meet deadlines within tight timelines
• Knowledge in machine learning industry needs, trends, and employability
• Possess a growth mindset and be able to receive feedback

Compensation: This role is on a per assignment model of $4.50 per assignment graded