UPLOAD YOUR CV
We help the best talent in the Digital analytics market to find rewarding careers.
Simply upload your CV and select your areas of interest and our expert recruitment consultants will be in touchUpload Now
$150,000 - $170,000
Are you a Software Engineer with a desire to work for a hyper-growth, real estate-focused, investment management company that is sweeping the nation? Do you want to work with large quantities of data to drive business decisions for the better? This is an incredible opportunity with an amazing company, to use the full scope of your software engineering abilities.
This investment manager is changing the way housing rentals are operated in the United States. They have recently seen an incredible amount of growth in their residential housing ventures. The scaling up occurring during a pandemic that was mostly harmful to this market is a testament to their mission and quality. This company is looking for skilled Software Engineers to provide the substance and applications they need to make data-driven decisions.
THE ROLE - Software Engineer
As Software Engineer, you will be working with data from various aspects of the housing market. You will be expected to work with unstructured data daily, perform statistical analysis in Python, and deploy it to AWS and Azure. You will also get the chance to work with performative data to identify trends in the housing market nationally. Further responsibilities include:
YOUR SKILLS & EXPERIENCE:
As Software Engineer you can expect to earn up to $170,000 (depending on experience), 401k, medical, dental, vision, and more.
HOW TO APPLY
Please register your interest by sending your resume to Danny Macdonald via the Apply link on this page.
£70000 - £75000 per annum
Lead Software Engineer role for a tech company that use advanced analytics to help their customers with purchasing decisions.
£90000 - £100000 per annum + Pension
This Chief Information Officer opening is for a famous UK charity who are embarking on a significant data transformation project.
US$150000 - US$170000 per year
This is a great opportunity for a skilled data leader to work at the intersection of sports and technology while guiding a data team.
£80000 - £100000 per annum + Bonus
Full Stack Engineer role for a Senior applicant who is still wanting to be hands-on. You will also be leading a team and shaping roadmaps.
With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.
Visit our Blogs & News portal or check out our recent posts below.
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. Computer Weekly: Why a cloud operating model matters Consulting firm Contino has said that, “successful cloud adoption requires organisations to go beyond tools and techniques to map out a cloud operating model”. Within this article from Computer Weekly, this idea is explored as greater emphasis is placed on the need for organisations to change the way they work to reap the full benefits of cloud technology. When looking to adopt a cloud operating model, companies should look to think about the cloud as a product, that serves a business need, and then align the team structures and relevant accountabilities accordingly. It’s a serious commitment – so reshuffling the team to make the best of the tech is critical. See more on bringing cloud tech into your business here. DevOps Online: Artificial Intelligence to play a more important role within DevOps We’re incredibly excited by this new research from GitLab, that has found out that Artificial Intelligence (AI) and Machine Learning (ML) are starting to play an important role within DevOps. Some of the top points from the study were: 84 per cent of developers and managers stating they’re releasing code faster than before and 57 per cent declared that code is being released twice as fast.12 per cent of respondents said that adding a DevOps platform has sped up the process, and 10 per cent said the same about adding automated testing.75 per cent of enterprises are using AI/ML to test and review their code before release, while 25 per cent use full test automation. The survey showcased that developers’ roles are shifting toward the operations side as they are focusing more on test and ops tasks, especially around cloud, infrastructure, and security.DevOps is an incredibly dynamic market, and one that we’re building our networks in, so we’ll be sure to keep an eye on how this develops. To read more on this topic, click here. Forbes: The five ways to build Machine Learning models Machine learning (ML) is powering most of the recent advancements in AI, including computer vision, natural language processing, predictive analytics, autonomous systems, and a wide range of applications. This insightful article from Forbes explores the five ways in which ML models can be built up: Machine Learning toolkitsMachine Learning PlatformsAnalytics SolutionsData Science NotebooksCloud-native Machine Learning as a Service (MLaaS) offerings. Knowing what different options are available and that there is no one-size-fits-all for ML will help businesses to make better decisions. To read the full article, see here. CMI: How to become fluent in diversity and inclusion: keep practising In this interesting interview, CMI Companions talks about how leaders can move from othering and executive-level disinterest to action and organisational survival. The core questions that came up from this discussion covered: So why are we still seeing a lack of diversity in so many organisations?How can leaders and organisations move from seeing diversity as a challenge to seeing it as central to performance and survival?What can you do to become a leader who’s fluent and effective when it comes to diversity and inclusion? Through the panel discussion, the leaders explored creating inclusivity in a virtual environment, focusing on retention, promotion and growth and making diversity and inclusion a priority within the business. To read more about this, click 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.
04. June 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