Data Scientists
General
- Bootcamp
- 10 learners; teams of 4
- 80 hours per learner
- Dates set by experience
- Learners self-assign
Preferred companies
- 5/7 project matches
- United States
- Academic experience
- Any
- Any
Categories
Skills
Project timeline
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January 30, 2023Experience start
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February 5, 2023Kick Off Meeting
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February 7, 2023Finalize Project Plan
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March 2, 2023Mid-Point Check in
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March 4, 2023Final Presentation
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March 4, 2023Experience end
Timeline
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January 30, 2023Experience start
-
February 5, 2023Kick Off Meeting
Meeting between students and company to develop a more detailed project plan and confirm communication styles, and important dates.
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February 7, 2023Finalize Project Plan
Submit and finalize the project plan outlining the major deliverables, division of labor, and timeline.
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March 2, 2023Mid-Point Check in
This is a time to more formally touch base.
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March 4, 2023Final Presentation
Deadline to present final findings and make sure work and materials produced during this project are seamlessly handed off.
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March 4, 2023Experience end
Overview
- Details
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Looking to elevate your organization, and bring it to the next level? Bring on learners from Springboard's Data Science Bootcamp to be your student-consultants, in a project-based experience. Students will work on one main project over the course of the semester, connecting with you as needed with virtual communication tools.
Students in this program go beyond just the technical skills, to focus on areas where employers find the biggest gaps -- strategic thinking, problem-solving, and communication. Students have an analytical mindset and are ready to work with your company with their technical skills and business and professional prowess. They possess an excellent understanding of data visualization, data storytelling, and how to think about data problems in a business context.
Springboard data scientists typically have about 3 years of professional experience before enrolling in the 9-12 month course. They demonstrate real-world experience while helping solve a business problem.
- Learner skills
- Machine learning, Data analytics, Data science, Natural language processing
- Deliverables
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Deliverables are negotiable, and will seek to align the needs of the students and the client.
Some final project deliverables might include:
- A 10-15 minute presentation on key findings and recommendations
- A detailed report including their research, analysis, insights and recommendations
Project Examples
Students in groups of 3-5 will work with your company over 6-8 weeks to identify your needs and provide actionable recommendations, based on their in-depth research and analysis.
These are fully remote services and companies of all stages are welcomed. We ask that companies with interest in hosting a Springboard Data Science student have access to relevant data necessary for execution of the project and have a data scientist, or someone with a related background, on staff.
Project activities that Springboard students can complete may include:
- Data cleaning and wrangling
- Data analysis
- Modeling and experimentation
- Predictions
- Insights
- Live Visualizations
Common Business Problems requested to be solved include, but are not limited to:
- Predicting customer churn
- Predicting how much revenue you’ll get from any individual customer
- Predicting which patients will be re-hospitalized after a stay / Predicting which patients are at the highest risk for a poor health outcome
- Predicting company revenue (time-series)
- Predicting activity from wearables data
- Investigating why there was a big change in customer activity
- Investigating what’s the fastest area of revenue growth
- What factors are related to revenue growth?
- Are your services priced competitively / appropriately?
- What is your largest manufacturing costs? What are your areas of greatest cloud spending?
- Visualizing survey data for employee satisfaction from HR (~60k employees) without needing to read every response
- Get back a lot of data from the devices out in the field
- Figuring out ways of visualizing battery life from devices of different ages (can see what is going on right now, and how does it change over time?)
- Using Excel to create a default financial analysis module covering revenue and operational cost modelling.
- Financial concepts including revenue, cost of goods sold, profit, balance sheets, cash flow statements, income statements and EBIT
- Economic concepts including supply and demand curves, cost curves
- Statistical concepts including descriptive statistics (mean, mode, standard deviation, correlations etc.), correlations, simple and multivariate regression, confidence intervals
Additional company criteria
Companies must answer the following questions to submit a match request to this experience:
Provide an opportunity for students to share their work on job search materials; redactions of confidential information can be discussed.
How does the project/ business problem you are hoping to have solved, benefit the data scientists in their job search?
Provide relevant information/data as needed for the project.
Provide a dedicated contact person who is available for weekly/bi-weekly check-in meetings to unblock the team, provide feedback, as well as periodic messages over the duration of the project.
Does your company have an established data team or data individuals who will work with students in this project?
Be available for a quick phone/virtual call with the instructor to initiate your relationship and confirm your scope is an appropriate fit for the course.