What’s it like to work together?

  • We are a small team behind the work that’s produced by data-mania.com. Our mission is to support data professionals in transforming to world-class data leaders and entrepreneurs. Our focus is on helping our students and clients get massive wins (AKA promotions, pay raises, and improved profits) in the shortest amount of time, with the least amount of effort, by executing our proven strategies.
  • We are hard workers and careful workers. We expect the same from every person on the team. We believe in taking smart action (aka; an optimized approach) to all work that’s done within the business, and there is a lot of it. We expect 110% effort (and attention to detail) in everything that each team member does. Each member of the team is expected to go above and beyond. We aren’t minions. As a team member, we’d expect you to “do the work” but also, to share your thoughts about how the work you do can be better utilized to grow the business.
  • We are transparent and humble. Consequently, we’ve built incredible trust within the team. This trust and humility is reflected within the internal communications of the team, as well as the way we communicate publicly with our audience.
  • We are obsessed with doing less, better. Naturally, as a data business, we’re always looking for ethical, strategic ways to optimize our approach to business – in order to produce better results with less effort. We encourage all team members to consider how their tasks and workflows impact the businesses bottom-line, and how those tasks and workflows can be optimized to grow the business faster.
  • Quality over quantity – always. We are laser-focused on quality communications within the team. This means, there is no room for vagueness, assumptions or complaining from team members. We are also laser-focused on the quality of our deliverables, content, products, and services. We are committed to creating meaningful, relevant, and comprehensive content that truly helps our customers achieve they’re transformation as effortlessly as possible. This is achieved through deliberate attention to detail in all aspects of our work, including communications, content marketing, product design, and delivery.


Data Science Product Developer


This is an online remote position. Preference will be given to native English speakers, but this position is open to people from all countries and walks of life. There are no set hours for this job – you work when you want, from wherever you want.

Type of Position:

Part-time freelance contractor role starting at an expected 25 – 30 hours per month. We have one project we need support with currently, and there is a significant chance for this role to grow to a much larger capacity within the company.

Overview of Position:

As the Data Science Product Developer, your responsibility will be to execute tasks related to updating our data science course curriculums, books, digital products, and ebooks. You will also work to develop new data science products for internal use, and for use by our customers. Your role helps ensure that the business’s courses, books, and data products are well-maintained and are of optimized-design (meaning that they achieve the most powerful results in the shortest amount of time for our clients). 


  • Assess existing data science products and make recommendations for improvements.
  • Draft implementation plan for the revision of existing data science products or the build-out of new data science products 
  • Implement the data science work that is needed to execute upon your implementation plans
  • QA/QC the data science products you develop or revise
  • Make suggestions for new hires, in cases where work is beyond your scope of expertise
  • Suggest new data science products that you think would help our customers achieve quicker, easier transformations
  • Develop plain-language documentation and written scripts that support each and every facet of the data science products you revise or build.

Results (expected accomplishments):

  •  Produce revision recommendations and plans
  •  Implement the data science that’s necessary to revise existing products, or develop new ones.
  • Understand our programs and customers such that you grasp the different types of transformations they seek to achieve.
  • Extraordinary attention to detail when it comes to reviewing, planning, coding, and writing / documentation  – to ensure that our products are laser-focused on getting results for our clients (all value, no filler, no fluff)
  • Write (or re-purpose) detailed training documentation that supplements each aspect of the data science products we deliver
  • Submit a monthly progress report to the team to reflect on the week, sharing any important metrics

Requirements (expected proficiencies):

  • Excellent communication skills, especially in writing. You should be able to explain complex topics in plain, easy-to-understand language. and have the ability to express complex topics clearly and easily. You are fluent in English, and have a handle on the modern idiosyncrasies involved in communicating within the norms of hip, American remote-workers.
  • You love what data can do for people and for businesses: You’ve got 1-2 years of experience working as a data science professional. You have expertise in Python, related Python libraries (pandas, numpy, scikit learn) Jupyter notebooks, and Python Dash.
  • You have taken college-level courses on statistics, mathematics, and probability. You know how to build and apply statistical machine learning models in python, using libraries like scikit-learn and statsmodels.
  • You have experience in statistical hypothesis testing as well as experimental design, data storytelling, data visualization techniques / tools, and the manipulation of large sets of (sometimes sparse) data.
  • You are skilled at both demonstrating and explaining how machine learning algorithms work.
  • You’re extraordinarily detail-oriented. You have incredible organizational skills – with respect to both content organization and how you organize your projects, processes, and workflows.
  • You’re collaborative. You love the freedom of working remotely, and love working across cross-functional teams
  • You are passionate about data and data science product development
  • You do not want to be the star of the show; you’re more happy working to support the business behind-the-scenes 
  • You are loyal and hardworking. You do not get flustered when priorities change quickly
  • You are a self-starter. You don’t need much, if any supervision. You don’t expect much, if any, facetime.

Bonus points if you have:

  • Deep learning expertise
  • Marketing data science expertise
  • Content marketing subject matter expertise
  • Social media marketing subject matter expertise

Please do NOT apply if:

  • You already own and sell data science products online OR if you are already working for a similar or competing company
  • You don’t naturally take time to QA/QC all your (work / comms / submittals) before you submit them.
  • You use the word ‘kindly’ anywhere, ever.

Applicants must be experienced with using Slack, Jupyter Notebooks, Google Docs, Google Sheets, Google Drive, and Zoom.

We manage our projects in Airtable (which is essentially an online SQL database with added project management features). You must be comfortable learning to use that tool, if you haven’t already.

You tell me your hourly rate requirement, but maximum starting pay for this position is $25 USD per hour, depending on experience. This is an independent contractor position (no employee-employer relationship is implied). There is a 90-day trial period.

Click the “Apply Here” button below to apply. Please make sure to type your name in all caps.

Within your application, please provide as much explanation as possible. “Yes” and “no” only answers will not be given credit. Please use this application as an opportunity to create a first impression and let me know why you are the best applicant for the role.

DEADLINE TO APPLY: Friday July 30, 2021.

I will email you if you make the short list. Thanks in advance!


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