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Waitlist: Mentor - Data Science Career Track (Part-time/Remote)

Remote
Please note: we are currently at capacity for Data Science Mentors. However, we’d still love to connect with you! By applying to this role, you will be added to our Course Mentor waitlist. We will contact you as soon as we re-open our hiring process.
 
The Opportunity
Springboard runs online, self-paced, Python- and R-based Data Science workshops in which participants learn with the help of a curated curriculum and 1-1 guidance from an expert mentor.
 
Our mentor community - the biggest strength of our programs - comprises experts from the best organizations in the world. Our mentors range from data scientists and researchers at premier companies (Uber, Pandora, LinkedIn, Apple) to a wide variety of top-notch startups and consulting firms.
 
If you are as passionate about mentoring as you are about Data Science, and can give a few hours per week in return for an honorarium, we would love to hear from you.
 
The Program:
  • Completely online
  • Most are designed to be complete in 3-6 months or less, depending on the course
  • Participants in this course are working professionals and college students from all over the world, interested in getting started with data science.
  • Participants learn about Data Science with the help of a curated online curriculum and a personal mentor. They go through the curriculum at their own pace and have a weekly 30-minute checkin with their mentor to discuss questions, projects, and career advice!
  • Students communicate with mentors outside of calls on an as-needed basis to support learning and career objectives
You:
  • Are as passionate about teaching Data Science as you are about Data Science itself
  • Are that rare combination of programming, statistics and storytelling skills
  • Are proficient in the curriculum topics of at least one of our programs: Data Science Career Prep and/or Data Science Career Track (taught in Python)
  • Are available for weekly, 30-minute video check-ins for each student to help them set and achieve learning goals, provide feedback, and help them move towards getting a job
  • Are able to utilize Zoom for the 30-minute calls with students
  • Are available outside of weekly calls for each student to review projects and answer questions as needed
  • Have at least 2 years of experience solving real-life data science problems, and are comfortable working with large data sets
  • Are empathetic and have excellent communication skills
Benefits:
  • Membership in a rich community of expert mentors from great companies like Apple, Uber, and Pandora
  • Change the lives of students in our program
  • Help us revolutionize online education!
  • Receive a monthly per-student honorarium
  • Work at your convenience

We are an equal opportunity employer and value diversity at our company. We welcome applications from all backgrounds, and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

California Privacy Rights Notice for Job Applicants
Under the California Consumer Privacy Act (“CCPA”), Springboard is required to inform California residents who are job applicants about the categories of personal information we collect about you and the purposes for which we will use this information. This notice contains disclosures required by the CCPA and applies only to personal information that is subject to the CCPA.

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Unit 1: Python and its standard libraries, Matplotlib and Seaborn Visualizations, writing clear, elegant, readable code in Python using the PEP8 standard

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Unit 2: Pandas to wrangle and clean data, working with different file types from text to Excel, CSV and JSON, relational and non-relational databases, SQL skills, APIs

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Unit 3: Presenting insightful findings from a data exploration, data storytelling

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Unit 4: Basic inferential statistics and parameter estimation, hypothesis testing to determine if phenomenon is statistically significant, correlation and regression, A/S split tests, exploratory data analysis

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Unit 5: Scikit-learn to implement supervised and unsupervised algorithms, time series analysis and social network analysis, random forests and gradient boosting, validating and evaluating machine learning systems

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Unit 6: Understanding of Big Data, MapReduce, Spark, MLib, NoSQL

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