Clean Technology Meets Data Science: News and Articles

  Have you looked at our  jobs portal  recently? Or explored openings and roles at the intersection of clean technology and data science?   Something strange has been happening over the last quarter - something that we really haven’t seen for the last couple of years. Many positions in large companies and startups that were posted late last year have been reposted again this quarter. And not just that, we’re seeing several openings posted on job sites and go unfilled despite repeated postings and connections with different networks.     So, this month, let’s go a little deeper and see what’s happening in the market.     For the last couple of years, we’ve been seeing a steady growth in roles for data scientists, modelers, program managers, C-level positions in companies in agriculture, energy, sustainability and water sectors. Initially, as we would have expected, we saw a lot of positions in newer companies - companies like Climate Corporation, Opower, Blue River Technology and so on.

  Here's wishing all our readers a very happy new year!  Last year, we started our journey to making data science accessible for people interested in clean technology and solving the problems facing our planet.  We had the pleasure of conducting several workshops and online webinars on different aspects of data science in clean technology. We covered a wide range of topics in our in-person workshops where we discussed data sources in different clean tech sectors, how to build effective algorithms and models including deep learning, and presented uncertainty analyses and business use cases. We also began conducting online sessions in the latter half of the year where we introduced folks to careers and tools at the intersection of data science and clean tech.  As part of our expansion plans in 2020, we're creating an online education platform that focuses on applying data science effectively in clean tech sectors. We're in beta this month and are building our content which wi

  Is data science infallible? If all we had to go on were the breathlessly excited articles published in business magazines and the highly polished releases from startups and large tech companies, it would certainly seem so. Think of the articles that have been published this year with titles like -     “Artificial Intelligence (AI) to replace all jobs by such and such year”, “Machine learning solves problem faster than humans”,     “ Data science shows promise to end world hunger soon” - and so on and so on….  Data science is a relatively new field, but one that combines elements from disciplines that have been around for a while - computer science, statistics, and algebra for example. The difference right now is the sheer power and availability of computational resources like the cloud that allow people to build and run different models and experiment on a scale that we haven’t seen before. And in high-tech companies, we’re also seeing an explosion in the availability of data that al

  If you had to pick a buzzword for 2019 in clean technology and data science, it would be “Smart Cities”!     This year, we’ve heard about Alphabet’s Sidewalk Labs and their efforts to design one in Toronto; India and China have announced plans to redesign over 100 cities into “Smart Cities”; European countries like Norway and Finland highlight the fact that much of what is touted as a “Smart City” already exists in their systems; and plenty of people in Silicon Valley have their own ideas of what Smart Cities should be like and what they should do.     A couple of features do stand out in many of the conferences and presentations about Smart Cities - 1) Opportunities abound with an estimated market size of   $237 billion by 2025 according to one study   and 2) There’s a wide range of interpretations about what exactly makes a city “Smart”.   The most conservative definition and the one that governments and city organizations highlight is “ where traditional networks and services are

  There's an interesting conference coming up in Sunnyvale, California on October 8th. The topic is "Smart Cities Innovation Day: A future outlook on urban life". The location is at one of the Valley's incubators - Plug and Play and the agenda promises to be quite interesting! Several startups are presenting, there's a panel discussion with officials from regional and city governments, and a keynote from the head of IoT at the World Economic Forum.    If you're curious, the link to register is   here.  

  Let's get back to talking about wildfires! This is the second of our two post series on wildfires, data science and what we can do about them.   In the first post, we talked about satellite data and how it is used to track wildfires - especially large ones like we see in the Amazon this year. The wildfires burning in the Amazon have slipped off the front page of most newspapers, but they're still burning. And let's not forget the opposite end of the globe where wildfires in Indonesia are also burning out of control! The interesting aspect about wildfires and natural disasters in general is that most of the attention and resources are focused on dealing with them as they are happening and figuring out what resources are needed and what changes are needed after it's all over.  So, we see a lot of effort focused on satellite imagery, understanding wildfire extents after they have started, building apps and websites for people to access resources and tools during and afte

I'm excited to have been invited by the organization "Women in Big Data" to talk about data science, agriculture, the environment and all the associated challenges. The symposium is on Wednesday, September 18th at Sacramento, CA and you can expect a lively discussion with me and three other experts on the panel! If you're interested, event details are at https://www.eventbrite.com/e/symposium-using-data-to-sustainably-feed-the-world-tickets-72188915991 . For all of you who are curious,   Women in Big Data   is a grassroots organization that started in Silicon Valley with women from different organizations who work in data science coming together to talk about the technical challenges, career pathways and entrepreneurship and funding among other fun topics. The group started with 5 women and now has close to 14,000 members all over the world - which is an amazing growth rate over the last 3 years! They hold conferences, regular meetups and training sessions and the one