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Federal Consulting Firm
$170,000 - 190,000
A top federal consulting firm that provides data & analytic solutions around machine learning, data engineering, enterprise architecture, and BI. They work with the largest enterprises and government agencies.
THE ROLE - Cloud Engineer
As a Cloud Engineer, you will partner with sales teams and be responsible for all technical aspects. Building data pipelines, cloud architecture, data quality, data management, and API's. Your responsibilities will include:
YOU WILL NEED:
HOW TO APPLY
Please register your interest by sending your resume to Jacob Ragland via the Apply link on this page.
AWS, Python, Data Engineering, Cloud Engineer, Pre Sales, Data Warehouse, Data Management, SaaS, Cloud, BI, Consulting
£60000 - £75000 per annum
Join our client and become a specialist Software Engineer in their Mobile Platform Team!
€680 - €760 per day
Amsterdam, North Holland
A leading Dutch Bank is looking for a Data Engineer to join their Data Engineering for Credit Risk team.
£60000 - £70000 per annum
This is an exciting opportunity to join a fast-growing tech company that have put data at their forefront.
€77467 - €99600 per annum
We are looking for a Lead Data Consultant to mentor our data and analytics team and drive our data competency to a new level.
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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This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics. Personnel Today: Mental Health Awareness Week: Concerns up 24% from last year It was Mental Health Awareness week this week, and this year, the focus was on the theme of nature. Personnel Today revealed some worrying statistics on the back of research from Close Brothers into the state of the population’s wellbeing in 2021. Reports of mental ill-health has increased by nearly a quarter since this time last year as a direct consequence of the stresses and strains of COVID-19. From yo-yoing in and out of lockdowns to extended periods of isolation, job uncertainty and illness, this year has been like no other and it’s most certainly taken its toll. 63 per cent of 16–34-year-olds report mental health worries, up a seventh from last year.For those who are 55+, this worry has risen by a third. In this piece, it is made clear that the underlying issue lies not only with COVID-19, but the lack of support given by employers. The research revealed that 70 per cent of employers don’t have a wellbeing budget in place, and only 8 per cent of firms invest more than £126 per employee each year in health and wellbeing. To read the full research, visit Personnel Today here. Towards Data Science: 5 unique skills every Data Scientist should know We know that career tip articles for Data Scientists can all feel pretty ‘samey’. But this article in Towards Data Science mixes up the usual advice, looking at how those in, or aiming to be in, the industry need to brush-up on their softer skills if they are to be successful. Tips include: Cutting down the jargon in order to communicate effectively with stakeholders. Don’t be hasty to overpromise, or you’re at risk of seriously under-delivering. Become friendly with your team’s software engineer, they’ll only be able to help you be more efficient and effective in your role. Of course, there has to be some mention of coding in there – it wouldn’t be a data-based article without it. Make sure you’re mastering your SQL Optimisation. Don’t leave your Git out in the cold, become familiar with the practice to ensure you can update your model code quickly. To read the full article, click here. Analytics India Mag: What SMBs can learn from Big Tech’s AI playbook? AI has come on leaps and bounds in a short space of time, and its popularity has boomed. For the monster-sized companies, where budget is of no question and innovation can happen overnight if need be - embracing AI has been a total no-brainer. Workflows become more efficient, technology becomes smarter, and the scope of growth seems infinite. However, despite all the benefits of AI that are so regularly shouted about, it’s been clear since the birth of the technology that there’s a huge divide in those who can and those who cannot afford to implement this innovation. Up until now. In this piece from Analytics India Mag, author Ritka Sagar, highlights how SMEs are finally finding ways to become ‘inventive’ with how they implement and use AI systems without breaking the bank. To read how SMEs are managing this, click here. Silicon Republic: For smart cities to work, they need to be neutral and objective The concept of a smart city seems like something out of a futuristic, sci-fi film but, in fact, they are closer to becoming a reality than we may think. The idea being that urban areas use sensors and other electronic methods to collect data. From citizens to traffic, water supply networks to crime detection, all of these assets of life, and more, are monitored, data collected, and insights given to make ‘life’ more efficient. On the surface, it’s all very cool, but there are, of course, worries that come with it. In this Silicon Republic article, Computer Scientist, Larissa Suzuki, discusses the importance of ‘neutral and objective’ smart cities if they are to work. She says; “Data and services in smart cities must be neutral and objective when reporting information about the city environment. They should encompass the entire population and respect data licences, regulation and privacy laws,” she said. “In a similar fashion, the digital services and the backbone technology – including algorithms – should be free from any ideology or influence in their conception, operation, integration and dissemination.” To read more on the future of smart cities, visit Silicon Republic here. We've loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at email@example.com.
14. May 2021
We recently spoke Nisha Iyer, Head of Data Science, and Nupur Neti, a Data Scientist from Data Society. Founded in 2014, Data Society consult and offer tailored Data Science training for businesses and organisations across the US. With an adaptable back-end model, they create training programs that are not only tailored when it comes to content, but also incorporate a company’s own Data to create real-life situations to work with. However, recently they’ve been looking into another area: toilet paper. Following mass, ill-informed, stock-piling as countries began to go into lockdown, toilet paper became one of a number of items that were suddenly unavailable. And, with a global pandemic declared, Data Society were one of a number of Data Science organisations who were looking to help anyway they could. “When this Pandemic hit, we began thinking how could we help?” says Iyer. “There’s a lot of ways Data Scientists could get involved with this but our first thought was about how people were freaking out about toilet paper. That was the base of how we started, as kind of a joke. But then we realised we already had an app in place that could help.” The app in question began life as a project for the World Central Kitchen (WCK), a non-profit who help support communities after natural disasters occur. With the need to go out and get nutritionally viable supplies upon arriving at a new location, WCK teams needed to know which local grocery stores had the most stock available. “We were working with World Central Kitchen as a side project. What we built was an app that supposed to help locate resources during disasters. So we already had the base done.” The app in question allows the user to select their location and the products they are after. It then provides information on where you can get each item, and what their nutritional values are, with the aim of improving turnaround time for volunteers. One of the original Data Scientists, Nupur Neti, explained how they built the platform: “We used a combination of R and Python to build the back-end processing and R Shiny to build the web application. We also included Google APIs that took your location and could find the closest store to you. Then, once you have the product and the sizes, we had an internal ranking algorithm which could rank the products selected based on optimisation, originally were based on nutritional value.” The team figured that the same technology could help in the current situation, ranking based on stock levels rather than nutritional value. With an updated app, Iyer notes “People won’t have to go miles and stand in lines where they are not socially distancing. They’ll know to visit a local grocery store that does have what they need in stock, that they’ve probably not even thought of before.” However, creating an updated version presented its own challenges. Whereas the WCK app utilised static Data, this version has to rely on real-time Data. Unfortunately this isn’t as easy to come by, as Iyer knows too well: “When we were building this for the nutrition app we reached out to groceries stores and got some responses for static Data. Now, we know there is real-time Data on stock levels because they’re scanning products in and out. Where is that inventory though? We don’t know.” After putting an article out asking for help finding live Data, crowdsourcing app OurStreets got in touch. They, like Data Society, were looking to help people find groceries in short supply. But, with a robust front and back-end in place, the app already live, and submissions flying in across the States, they were looking for a Data Science team who could make something of their findings. “We have the opportunity,” says Iyer “to take the conceptual ideas behind our app and work with OurStreets robust framework to create a tool that could be used nationwide.” Before visiting a store, app users select what they are looking for. This allows them to check off what the store has against their expectations, as well as uploading a picture of what is available. They can also report on whether the store is effectively practising social distancing. Neti explains, that this Data holds lots of possibilities for their Data Science team: “Once we take their Data, our system will clean any submitted text using NLP and utilise image recognition on submitted pictures using Deep Learning. This quality Data, paired with the Social Distancing information, will allow us to gain better insights into how and what people are shopping for. We’ll then be able to look at trends, see what people are shopping for and where. Ultimately, it will also allow us to make recommendations as to where people should then go if they are looking for a product.” In addition to crowdsourced information, Data Society are still keen to get their hands on any real-time Data that supermarkets have to offer. If you know where they could get their hands on it, you can get in touch with their team. Outside of their current projects, Iyer remains optimistic for the world when it emerges from the current situation: “Things will return to normal. As dark a time as this is, I think it’s going to exemplify why people need to use Artificial Intelligence and Data Science more. If this type of app is publicised during the Coronavirus, maybe more people will understand the power of what Data and Data Science can do and more companies that are slow adaptors will see this and see how it could be helpful to their industry.” If you want to make the world a better place using Data, we may have a role for you, including a number of remote opportunities. Or, if you’re looking to expand and build out your team with the best minds in Data, get in touch with one of expert consultants who will be able to advise on the best remote and long-term processes.
14. April 2020