The next decade will see the emergence of strange new job “data trash engineer” will arrive to replace those made obsolete by robots and automation, but the report’s authors warn that they’ll require society to handle a big shift in education and training. There has been plenty of fear in recent years about the rise of artificial intelligence, with forecasts suggesting that anything from 33 per cent to 50 per cent of certain jobs at risk of being taken over by machines.
In the report, it outlines the professions that will appear in the future as society adapts to a more automated and highly digitised world, with many of them reading like something from a sci-fi film or dystopian novel. With names like “head of machine personality design” and “flying car developer,” some of them are fairly self-explanatory and already semi-familiar, yet others suggest that the future will be a very strange place indeed.
Data Trash Engineer
Summary:
The theory behind junk data is often wrong, and we need to fix it. Data that has not been used by anyone in the past 12 months, has no foreseeable use as initially imagined, and isn’t necessary for regulatory purposes, can still be turned into insights. Just like food waste is a carbon that can be used to produce green energy, data waste is still meaningful if cleaned.
We’re seeking data trash engineers who can identify unused data in our organization, clean that data and feed it into machine-learning algorithms to find hidden insights by not only increasing how much data is collected, but also improving the data quality.
In the end, the goal of the data trash engineer is to transform data from trash to treasure. The possibilities are endless, and we expect the employee in this role to originate award-winning ideas.
What it takes to become a Data Trash Engineer?
In today’s business world, we often struggle to manage the ever-expanding volume of data around us, while also ensuring the quality of that data. As a result, we often end up labelling piles of data as waste if it hasn’t been used in the last 12 months. However, if we mine, refine and distribute it, data trash can be profitable, and the return on investment can be significant.
As a key member of a fast-paced, high-performing and highly-visible data analytics team, the data trash engineer will have the opportunity to use quantitative skills and develop well-rounded business insights by working across various functions on impactful, business-focused projects.
In this role, you’ll apply analytical rigor and statistical methods to data trash in order to guide decision-making, product development and strategic initiatives. This will be done by creating a “data trash nutrition labelling” system that will rate the quality of waste datasets and manage the “data-growth-data-trash” ratio.
For instance, if we’re expecting 30% annual growth in data over the next 12 months, the data trash engineer will ensure 30% of the data labelled as trash is cleaned and translated into key business decisions. In the end, this role will help us fix the data trash problem by establishing a ”trash-to-treasure” data supply chain.
What exactly Data Trash Engineers do?
- Create a data trash nutrition labelling system to rate the quality of each dataset. Perform end-to-end analyses that include business requirement specifications, data cleaning, analyzing, modelling, validating and facilitating gradual improvements.
- Become a champion of the “trash-to-treasure” innovation program by helping business teams find new opportunities, enhance customer interactions and uncover new business models. Review, analyze and share results to guide improvements, decision-making and program optimizations.
- Design AI test experiments that focus on enhancing customer experiences of our offerings, services and programs, as well as offer consultation and closely monitor experiment execution. The data trash engineer will ensure an uninterrupted supply of clean data is available for AI technologies to deliver the required results.
- Participate in the planning and strategy of key business projects by making business recommendations with effective presentations at multiple levels of stakeholders through visually compelling analytical results from the trash-to-treasure program.
- Drive collaboration and partnership with other data teams to ensure customer success.
- Partner closely with our legal teams to ensure we’re treating all customer data to comply with appropriate confidentiality and usage.
“The goal of the data trash engineer is to transform data from trash to treasure. The possibilities are endless, and we expect the employee in this role to originate award-winning ideas”.
SKILLS & QUALIFICATIONS:
- A master’s degree in a quantitative discipline (e.g., statistics, computer science, quantitative psychology, applied mathematics).
- Three to five years of experience with various data analysis tools, data mining tools and statistical packages.
- Experience working on big data and machine learning technologies, such as Azure Cosmos DB, TLC, Azure ML, Cortana Analytics, R, Python and SQL.
- Proficiency with analytical tools (R, SAS, Matlab, Python or Stata).
- Development experience in at least one scripting language, such as Python, Java, C, C++, Ruby or Perl.
- Solid interpersonal, cross-organizational collaboration capabilities, as well as written, verbal and visual communication skills to present complex analytical results concisely and effectively.
- Experience developing data visualization offerings and dashboards.
Conclusion:
So far, we have learned what is Data Trash Engineering, what they do and how to become one by satisfying skills and qualifications.
