Zaid Tashman

Data Science Researcher

San Francisco, California

"Data is full of imperfections; it’s vital to capture the essential aspects of real-world processes in a model."

How I put change in motion

As a Data Science Researcher, I help clients solve challenging problems and drive decisions using cutting-edge data analytics. Data is full of imperfections, and it is vital to capture the essential aspects of real-world processes in a model and not manipulate the data into the right form for an algorithm.

The Accenture Labs Tech4Good program recently partnered with non-profit organization charity: water, which provides clean, safe drinking water to more than 11 million people in 29 countries. The organization builds sustainable, community-owned water projects, including small, community-managed water points in remote areas. When a water pump fails, many people in rural communities must walk several miles to a neighboring water system just to access clean drinking water. In addition, managing the logistics of repairing these systems can be complicated and inefficient, as there is no visibility when the pumps break down.

Charity: water captured more than 32 million data points from a fleet of remote cloud-connected sensor devices, but needed help developing the tools and the expertise to analyze and unlock the potential value buried in this data to improve the scale and reliability of their services.

As the lead Data Scientist on the project, my role was to process, analyze and model water-consumption data recorded from a network of water pumps in northern Ethiopia. Our team built an anomaly-detection system using Bayesian methods to help provide deeper, more accurate insights from pump cloud-connected sensors throughout the region. The system set the stage for a predictive maintenance solution in which charity: water can accurately predict and prevent failures in its water systems. Communities benefit from less pump downtime and charity: water can concentrate on using its resources to help more communities.

Read more about how we helped charity: water provide water to communities in need across the globe.

Learn more about Data Science careers.

A day in my life

My days are never the same, but here are examples of a “typical” day’s R&D tasks:

  • Reading technical papers.
  • Analyzing and modeling data.
  • Building proofs of concept and prototypes.
  • Testing hypotheses.
  • Iterating on gradually more complex models.
“We helped charity: water apply cutting-edge technology to provide water to communities in need.”

My advice

Spend a good amount of time talking to the client and understand their real need before you start hitting the keyboard and modeling the data.

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