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With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

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How Big Data and Risk Analytics Can Help Fight Climate Change

Data is all around us. We use it to calculate our calories and our steps to ensure a healthy body. We use it track our packages and ensure delivery to the right location. We look to it to check the weather for exercise, driving conditions, and in extreme cases, safety preparedness. But, could we use it to fight climate change? Could we use it to reign in swiftly rising temperature changes which could affect our food and ecosystems?  Greener Choices for Greener Products People have more choice than ever before. They also have information at their fingertips and can see at a glance the benefits or the drawbacks of purchases. From how their food is grown to how far their food is delivered to the practices of companies from oil and gas producers to the wearables on their wrist. Climate change and Big Data have been linked, but mostly to determine greenhouse gases and effects of pollutants. But with the rise of consumer advocacy groups, farm-to-table traditions, micro-and macro-farming, and a desire to know more about what we’re putting into our bodies, consumers are dictating greener options from the markets. The Business of Climate Risk Analytics As consumers take note of climate change, companies are merging knowledge of climate change risk into their financial decision making. How will climate change their business practices? How will it be scaled based on how climate science rules inform financial risk assessments not yet developed? The markets need just as much information as consumers when it comes to climate risk. These assessments are intended to businesses determine consequences, responses, and likelihood of the impacts of their actions. Enter climate risk analytics. Climate Risk Analytics uses risk assessment and risk management based on natural disasters and their impact. However, the climate is not in a static state. It’s ever-changing and those changes are often in the extremes with little information related to averages. This complicates risk assessments as do the differences in regional projections. How AI Can Help Big data combined with climate risk analytics is getting an additional boost from artificial intelligence. AI techniques are being used for a variety of situations such as disease tracking, crop optimization, and monitoring everything from our heartbeat to endangered species. Solutions from advances in Deep Learning and Machine Learning could solve global environmental crises while assuaging financial risk with predictive modelling. Yet barriers to effective solutions from AI include cost and regulatory approval. But if these items weren’t an issue? We could determine such vital information as water availability and ecosystem wellbeing. Water and ecosystems aside, AI can help: Track and monitor endangered speciesImprove energy efficienciesOptimize wildlife conservation Fight poaching of endangered speciesTrack mosquito populations to prevent diseaseWarn populations of upcoming storms• Inform agriculture, health, and climate studiesDetermine water, forest, and urbanization changesSome vineyards in California use AI to determine if vines receive enough or too much water. AI’s ability to process large amounts of information quickly are a boon to the ever-changing climate, its risk assessments for businesses, and its benefits to consumers and investors who want to know what businesses are doing to keep everyone safe. In Honor of Earth Day This week we celebrate Earth Day. It’s a day to remember and honor the earth who gives us our air, our food, our animals, plants, fish, and so much more. From Greta Thunberg’s School Strike for Climate to Naomi Klein’s book, The (Burning) Case for a Green New Deal, climate is front and center of our thoughts and our survival. Want to be part of the movement working with Climate Risk Analytics or the effect of Artificial Intelligence in our environment? Harnham may have a role for you. From Big Data & Analytics to the Life Sciences, there’s something for everyone interested in the Data industry. Check out our current vacancies or contact one of our expert consultants to learn more.  For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Elizabeth Sobel

Elizabeth Sobel

22. April 2021

Why You Should Always Be Learning In Data Science: Tips From Kevin Tran

Last month we sat down with Kevin Tran, a Senior Data Scientist at Stanford University, to chat about Data Science trends, improvements in the industry, and his top tips for success in the market.  As one of LinkedIn’s Top Voices of 2019 within Data & Analytics. his thoughts on the industry regularly garner hundreds of responses, with debates and discussions bubbling up in the comments from colleagues eager to offer their input.  This online reputation has allowed him to make a name for himself, building out his own little corner of the internet with his expertise. But for Tran, it’s never been about popularity. “It’s not about the numbers,” he says without hesitation. “I don’t care about posting things just to see the number of likes go up.” His goal is always connection, to speak with others and learn from them while teaching from his own background. He’s got plenty of stories from his own experiences. For him, sharing is a powerful way to lead others down a path he himself is still discovering.  When asked about the most important lesson he’s learned in the industry, he says it all boils down to staying open to new ideas.  “You have to continue to learn, and you have to learn how to learn. If you stop learning, you’ll become obsolete pretty soon, particularly in Data Science. These technologies are evolving every day. Syntax changes, model frameworks change, and you have to constantly keep yourself updated.”  He believes that one of the best ways to do that is through open discussion. His process is to share in order to help others. When he has a realisation, he wants to set it in front of others to pass along what he’s learned; he wants to see how others react to the same problem, if they agree or see a different angle. It’s vital to consider what you needed to know at that stage. Additionally, this exchange of ideas allows Tran to learn from how others tackle the same problems, as well as get a glimpse into other challenges he may have not yet encountered.  “When I mentor people, I’m still learning, myself,” Tran confesses. “There’s so much out there to learn, you can’t know it all. Data Science is so broad." At the end of the day, it all comes down to helping each other and bringing humanity back to the forefront. In fact, this was his biggest advice for both how to improve the industry and how to succeed in it. It’s a point he comes back to with some regularity in his writing. “It doesn’t matter how smart you are, stay humble and respect everyone,” one post reads. “Everyone can teach you something you don’t know.” Treating people well, understanding their needs, and consciously working to see them as people instead of numbers or titles—this, Tran argues, is how you succeed in the business. To learn and grow, you must work with people, especially people with different skills and mindsets. Navigating your career is not all technical, even in the world of Data. “The thing that cannot be automated is having a heart,” he tells me sagely. Beyond this, Tran stresses the need for a solid foundation. The one thing you can’t afford to do is take shortcuts. You have to learn the practicalities and how to apply them, but to be strong in theory as well.  Understanding what is happening underneath the code will keep you moving forward. He compares knowing the tools to learning math with a calculator. “If you take the calculator away, you still need to be able to do the work. You need the underlying skills too, so that when you’re in a situation without the calculator, you can still provide solutions.” By constantly striving to collaborate and improve, Tran believes the Data industry has the best chance of innovating successfully.  If you’re looking for a new challenge in an innovative and collaborative environment, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

William Reichert

William Reichert

19. March 2020

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