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 News & Blogs portal or check out our recent posts below.
Whether you specialize in Credit Risk, Analytics, Data, Modeling, SAS, Insight, Data Management or Marketing Analytics, if you want to work on contract – this article will ensure you’re in the know.
The demand for contract workers continues to rise, especially within Data and Analytics, as flexible working becomes a way of life in many companies. Skills offered by professional contractors are highly valued by a wealth of organizations, many of whom see the procurement of short-term expertise as a key element in their recruitment strategy. Additionally, growing skills gaps in Data and Analytics have meant contract resource has become a necessity for many employers.
Contract work means that you are not employed on a permanent basis by anyone (Apart from your own Limited Company). You have the freedom and flexibility to decide when you want to work and for how long. Generally within our sectors and industries of focus contract roles range from 3 month assignments to 2 year contracts.
In today’s competitive business environment employers are turning increasingly to contract professionals to provide additional resources as and when they are needed as well as securing harder to find skill sets for specific projects. In fact, for some Data and Analytics skills such as SAS Analytics, Web Analytics, Marketing Analysis & Credit Risk, there is a real shortage of talent and that’s where you come in.
In addition, the flexibility, choice and variety of experience you can achieve by fulfilling contract or interim positions mean that this is an increasingly popular career choice for many professionals. As well as the career choice, contract work can also be an ideal solution for those between permanent jobs, traveling or looking to return to work after a career break.
There are two main options for contracting – you can either set up your own limited company or go through an umbrella company. Which one is for you? If contracting is a long term career choice then setting up your own Limited Company may be the best option as it is the most tax efficient way of managing your income. However, if you are only going to contract for maybe 3 – 6 month with the intention of then getting a permanent job, the utilizing an umbrella company will potentially be your best choice.
If you choose to set up a Limited Company which is the most common route then you will need to:
Become familiar with the constraints of IR35 and what contractual agreements you should and shouldn’t enter in to. If you are paying taxes like a Limited Company, you will need to behave like one, for example restrictions potentially exist concerning how long you can provide services for one client. Also your Limited Company needs the right to substitute its employees with other consultants.
Get a good accountant. Don’t cut corners - you really should do everything thoroughly and by the book. This is a real hot topic for the Government at the moment and you need to be familiar with and comply with all the latest regulations.
Think about the medium term when it comes to income, as a stable contract for 12 months at a market rate is far better than a very highly paid one for 3 months. It can take another 2 months to find that next contract and you could be unpaid for that length of time.
Be careful contracting through micro agencies (1 or 2 staff) if you can. If you do choose this route – you must credit check them. Some micro agencies can be financially risky - remember they are the ones paying you, not the client!
One of the big benefits of using agencies as well as an easy route to market for you is the fact they will normally pay you within 2 weeks of the end of the month you have just completed. Be aware contracting for companies directly can in many cases mean you are paid like a supplier and monthly invoices can take around 45 days to be paid in the UK.
Build your network
Lastly, build your network with all agencies, clients as well as other contractors. However you choose to contract – you are now the sales function for you and your skills and your network will have the have the knowledge of where your next contract is.
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 News & Blogs portal or check out our recent posts below.
What is it that makes California a mecca for the adventurous of spirit? Is it the land which sparkles gold from the goldrush years or the shiny newness of the latest in tech? From boom to bust and the promise in the dash of its life, it holds possibility in action. Or is it because, as other cities, states, and countries rally and evolve their own tech hubs, California has already settled in as the standard? The Golden State is the home of Data & Analytics. Want to see how high you can go or how to pull yourself up from a failed attempt at success? Look to the place it all began and learn how to make your insights actionable and your business decisions better. How? Begin with a platform. A Data Management Platform. You’ve Laid the Foundation, Now What? Rather than nuggets, blocks, or bars, Data gathering is cumulative. In this case, its divide, segment, and step back for the big picture; a Data Management Platform (DMP) is a unifying platform. In other words, raw Data is collated and changed into usable form. This is the core of Data-driven marketing. It is what helps businesses learn about their customers and helps to set the stage for the actionable insights that lead to happy customers. The abundance of Data can be staggering. How much of what information do you need to better manage your audience information? What do you need to know beyond the basics? How far should you drill down to shape and activate the Data you’ve been gathering and analyzing? Having the right Data reach the right customer at the right time can greatly improve a company’s bottom line. In layman’s terms, with a DMP as part of your marketing strategy, you’ll get the most bang for your buck. Making Connections Omni and multi-channel sources such as online, offline, and mobile are woven into the connections of DMPs. Unstructured Data collection is a neutral way to help marketers use their audience Data in whatever manner is best for their business. Sources come from first – and third – party sources including mobile, desktop, web analytics tools, Customer Resource Management (CRM) software, point of sale, social media, as well as the basics such as demographic and historical behavioral Data. Getting Started Organization – Determine how you want to define your Data so you can understand it when considering a DMP. How will you segment the information you’ve decided to collect?Segmenting and audience building – Once you’ve decided what information you want to gather, you can use the information to build your target audience. Imagine pinpointing a location on a map, then plotting a route to get there. Insights and audience profile reports – Here’s your chance to study the information and analyze patterns, trends, and intent. Let’s find out what exactly it is your customers want, so you can give it to them.Activation – Now, take what you’ve learned and run with it. This is the implementation phase whether it’s through advertising, messaging, even up your game and add-in the Data management platform information into your Content Management System (CMS). The possibilities are endless. Focus, Focus, Focus Here is where you’ll bring everything into focus and see just how far the possibilities can take you and your business. Below are a few ideas and things to consider: Set your audience and advertising targets – Determine the parameters for your audience’s interests and needs through the channels they most often use such as content whether audio or video.Get personal - Offer personalized experiences for web and mobile users as well as those who prefer to conduct their business offline.Game, Set, Match – When it comes to TV DMP, match your audiences on both TV devices as well as digital.Learn – Learn about your customer. Take time to get to know them online and offline through every channel available. Go deeper than point of sale information. What is it they’re looking for? What do they want? Why do they want it and how do they want to buy it? Grow – Whilst it takes a lot more time and effort to find new customers than to keep current customers happy it’s still important to use that time and effort to your advantage utilizing DMP to grow and cultivate a new audience, too. Build brand loyalty through both returning and new customers. Paid search and social – use your Data-driven audiences to target or update paid search including buys on social media. Ultimately, building a DMP will help you build a better relationship with your customers. It helps you show you have their desires at heart; and a happy customer is worth their weight in gold. Check out our current vacancies for our latest opportunities or contact one of our recruitment consultants to learn more. For our West Coast Team, call (415) 614 - 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to email@example.com.
13. March 2019
San Francisco is both a base and a destination for tech professionals. On the edge of Silicon Valley, its uniquely small-town-big-city vibe evokes a sense of community. For better or worse. Everyone is, essentially, in the same boat. But, here’s the thing. Everyone identifies and understands what the other is going through and what they might need assistance with. Imagine being a start-up founder, CEO, or tech genius and needing to spitball, vent, or discuss projects and frustrations. Who can you turn to? Why, the bigger and more established start-ups, CEOs, and enterprising entrepreneurs, of course. The ones who have been there and done that. If you can catch them before they jet off to their next business meeting in London or Beijing. It's also home to a number of world’s best Data & Analytics events, including the World Agri-Tech Innovation Summit in March. This San Francisco summit will host over 1500 agri-food corporates, innovators, and investors in the agri-food sector. It’s theme? ‘Turning Disruptive Technology into Business Strategy through Partnership and Collaboration’ AgriTech – The Newest Frontier of Digital Transformation? It’s not that new, really. This is its fifth year. But, what it is telling is that disruptive technology is playing a large role in agriculture. Remember when scientists were trying to figure out how to make seedless watermelon? Look how far we’ve come. This summit’s focus is on sustainable agriculture and items on the menu for discussion include: Best models for successful technology commercialization. Partnerships needed to scale new technologies. How to transform the food supply chain into a more sustainable, affordable, and nutritious systems for generations (spoiler alert: sayonara high fructose corn syrup, GMOs, and additives?). Best practices and case studies of opportunities for innovation and investment. To best address the above, speakers and attendees, will consider the above within the parameters of: Automation.AI-Backed Genomics.Biological Discovery Platforms.Predictive Agriculture. Several days in the making, it seems the above is probably just the tip of the iceberg. And, from the lab to the field, greenhouses, too are transforming as Artificial Intelligence helps decrease errors in manual Data collection. Using Predictive Analytics in Agriculture In a world driven to be sustainable, and to stem the tide of overabundance generated waste, digital and analytical products in the field have moved toward these endeavors. Imagine being able to calculate how much product is needed and only growing, and cultivating that amount. Using Predictive Analytics in agriculture not only helps ensure against error, but also provides predictive modelling, Data, and Machine Learning for predicting trends in the field. Armed with this information, a more stable bottom line may be found as well as more efficient use of on-farm products. Beyond the Buzz How will analytics affect future farming and create sustainable best practices for future generations? There are quite a few predictions at the table, and the answers are helping to drive actionable insights for decisions based on Data, improving: Product decisions.Product amount.Profitability. The 3 Ps are the what. Here is the how: Mini computers in our phones grant us information from the world and, with the right applications, can tell us our stock prices, how much milk is in our fridge, and even manage the heating and cooling of our home from afar. So, what if you could check on your field before ever leaving the house? Want to get a handle on pests? How about testing your soil’s value? These are just a few of the questions being asked and answered at the summit. This is the power of predictive analytics in agriculture. The World Agri-Tech Innovation Summit is in San Francisco from March 19th and 20th. If you’re interested in Biostatistics, Bioinformatics, Computational Biology, Big Data & Analytics, we may have a role for you. We specialize in junior and senior roles. Check out our new Life Science Analytics specialism or our current vacancies for additional opportunities. Contact one of our expert consultants to learn more. For our West Coast Team, call (415) 614 - 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to email@example.com.
28. February 2019
As the final few of months of 2018 approach, we’re starting to look to the year ahead. Since 2017, companies have begun to shift from data-generating to data-powered organizations, and it’s important to note how transparency practices, insights, and market spending are beginning to work together to deliver best value to a business and its customers. To plan effectively for 2019, marketing leaders need a solid understanding of the overall economic and competitive environment and the major trends impacting B2B marketing. In a joint effort, Duke University’s Fuqua School of Business, the American Marketing Association, and Deloitte, have created the CMO Survey, which seeks to capture senior level marketer’s opinions about important trends in marketing spending and practices. Drivers of Future Growth Survey participants were asked to rate the importance of five “drivers” of future organic growth in their business. They ranked the ‘right talent’ as their topmost priority whilst having the ‘right technology’ was listed only fourth out of the five possible choices. So, while technology remains an important driver, respondents clearly believe that having the right talent to work with that technology is the best way to deliver actionable insights and improve business performance. Blended within these marketing best practices are marketing spend, new roles which will come of age, and governmental regulations of transparency, specifically the European General Data Protection Regulation (GDPR). The latter, in particular, will see an increased prominence in the U.S. as customers demand more data protection and privacy. Changes to Marketing Spending Overall marketing spending is expected to grow by about nine percent over the next twelve months: Digital Marketing is expected to increase by up to 14%. Social media and mobile marketing are expected to increase rapidly but are unlikely to have a major impact on company performance. Despite this, we should see an uptick of around 7% within the next three to five years. Marketing analytics will also expand over the next five years, although marketing leaders are still working out how best to maximize analytics potential value. Introducing the Chief Data Officer There has been a rise in senior level roles with the Data industry. One of the most crucial, newly developed C-suite executive role is that of Chief Data Officer or CDO. Whilst the CDO’s role is to derive value from Data, this is not a functional role, but a strategic one. However, as this is still fairly new within the industry, any company appointing a CDO are clearly presenting their mindset as a Data-driven business. For those senior level Data professionals who understand agile platforms, methodologies, and can shift rapidly between centers of excellence and line-of-business, CDO could be your next role. Data Governance Professionals Though Data Governance strategies are key for all C-suite executives, there is also a place for an individual to hold a key role in Data Protection & Governance. Following the introduction of GDPR in May 2018, businesses were put on alert to take greater care of their customer’s data. Though fines are potentially massive, many enterprises, especially in the U.S. are still not prepared. It’s important now, and will become increasingly so, for organizations to get a better handle on the governance of their data assets. Extracting meaningful insights and increasing operational efficacy requires flexible, integrated tools that allow users to quickly ingest, prepare, analyze and govern data. Full transparency within an organization derives trust from customers and helps to draw more meaningful, timely insight conclusions. For more about the trends that have dominated 2018, you can learn more here. If you’re interested in Data & Analytics and are seeking a new role, we may have an opportunity for you. Let’s talk. To learn more, check out our current vacancies or get in touch: For the West Coast Team, please call (415) 614 4999 or email firstname.lastname@example.org. For the Mid-West and East Coast Teams, please call (212) 796 6070 or email email@example.com.
25. October 2018
If you’ve applied for a credit card or loan recently, you’ll be aware of the swift response you now receive. No human can crunch the numbers and make the determination that fast, right? Although big banks are now adopting Big Data, Machine Learning, and AI into their legacy processes, startups have been disrupting the sector for a few years now. As banks and credit unions scramble to keep up, Fintech innovation is bringing together machine language, analytics, and AI to help form Big Data decisions in the industry. The forward-thinking potential of these technologies has led to some real-world uses to combat fraud, offer access to alternative data sources, and suggest real-time analysis for risk. So, Robots are Determining My Credit Risk? Well, yes and no. Often, those in the financial sector are using AI to assess Credit Risk. What once required Risk Analysts to determine manually, is now done in a matter of seconds with an early warning system developed by ING, PwC, and Google. This AI-powered system helps analysts make faster and more informed decisions about potential risk. How do they do this? Using pre-set criteria, they can gauge and analyze risk based on parameters such as whether or not a client has negative media coverage or if a share price falls below a certain percentage. If the world today is based on perception, even such items as bad reviews, negative coverage, and lower than average share prices can affect determinates. In addition, having these parameters can also help determine best practices and how businesses and individuals can be given opportunities outside the scope of big bank processes. However, as data breaches continue to mar profiles of both individuals and business, Machine Learning components offer platforms the chance to stem the tide of negativity. How Machine Learning Helps Prevent Fraud This is a simple process which requires two key measures. The first is to feed the machine not just a large amount of data, but knowing the parameters set, so the machine is fed relevant information. The second is human input which gives the machine its parameters to operate by. From there, the software will take the information, gain an understanding of the data patterns, and identify any signs of fraud. If done well, the automation process will employ solutions without sacrificing quality. Machine Learning in Determining Scorecard Models Alternative data sources offer more options not only to banks and credit unions, but also to borrowers. Using Machine Learning creates a more flexible, robust model when it comes to the type of information most useful to various borrower profiles. Having profiles prepared allows for automated scorecard updates and can generate better responsiveness and intelligence of a borrower’s risk profile. This process can be empowering for both startup and big bank tech. The Matured State of Analytics Though humans must initially input parameters, the benefits of Machine Learning using a decision engine can dig deeper and reach farther than ever before. This type of platform can gather a variety of scenarios across the industry and can constantly analyze the information, helping inform the processes of setting credit limits, loan origination, and risk-based pricing. As an extension of a modern analytics platform, these processes fill in the gaps where other platforms may lack the data or programming required to run effectively. But, as these platforms mature, they are helping to drive innovation throughout the Fintech industry and shaking up the outdated, cumbersome processes of old for a much more streamlined efficient operation. Want to inform decisioning and work with data engineers to build validation frameworks? Are you looking to get in on the ground floor of a startup opportunity in the Fintech industry? If so, we may have a role for you. If you’d like to learn more, check out our current vacancies or contact one of our expert consultants to learn more. For our West Coast Team, call (415) 614 - 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to email@example.com.
21. March 2019