Ecommerce Insight Analyst
Manchester, Greater Manchester / £35000 - £45000
£35000 - £45000
Manchester, Greater Manchester
Digital Insight Analyst
Up to £42,000
Harnham are partnering with a national furniture and fashion retailer searching for a Data Insight Analyst to help build out their data maturity by combining offline and online data sources.
This company is a household-name in the fashion-industry with stores across the UK including a large retailer in Oxford Street. Having undergone a large period of growth over the recent years, they are looking to continue this trend by maturing their data capabilities and placing an increased importance on Digital.
As a Data Insight Analyst, you will be:
- Provide the business with in-depth customer analytics and insights including post basket analytics, web traffic performance analytics, customer journey analytics and looking specifically at drop-off rates.
- Combining offline and online data sources to ensure insights provided to the wider business can shape strategy moving forward.
- Building reports that compile e-commerce analytics, looking specifically at trading performance and sales reports.
Skills & Experiences
As a Data Insight Analyst, you will need to have:
- Commercial experience working with SQL through BigQuery.
- Experience working on web analytics projects, specifically using Google Analytics to analyse web performance. Any experience in Google Tag Manager is a big plus.
- Understanding of ETL and GCP platforms.
- Prior experience in an agency or retail environment is a big plus.
- Hybrid working.
- Opportunity for flexibility to implement your ways of working and strategy.
- Exposure to senior stakeholders.
Is Product Analytics the new Digital Analytics? | Harnham Recruitment post
Following on from our exploration of what Digital Analytics is, and the exploration specifically of hiring Digital Insights Analysts in the North of England and Midlands, we wanted to take a look at Product Analytics, and how it differs from the standard Digital Analyst role.To help investigate the importance of Product Analytics in the current market, we have interviewed Nicky Tran, a Product Analyst at Virgin Media (Manchester).What Is A Product Analyst?In simple terms, a Product Analyst ‘’looks at the different products a company has, and then you are identifying which areas of the product can be improved or which areas can be optimised.” While Digital Analytics can inform the product lifecycle, the interesting aspect to this role is, that unlike a traditional Web Analyst role, it is more of a hybrid role. Nicky emphasised that it is ‘’an upcoming sector within the analytics community’’, providing an overlap between Digital Analytics, Customer Analytics and Data Science.The key skills and tools for this role are advanced SQL, Google Analytics, and AB testing. So how does this skillset differ from a traditional Web Analyst? Nicky suggests that while the core requirements are that of a Web Analyst, with a web role you would essentially just be using Google Analytics Data. However, as a Product Analyst, you would be using advanced SQL to access other data bases, and pull data from models, and therefore, “you are combining two sets of data to get a more insightful look”.Why Is Product Analytics Important, And Why Are They Now Becoming More Prominent On The Market?Similar to Digital Analytics roles, it is clear that with the impending digital transformation, companies are becoming increasingly data-led, especially with regards to their digital platforms (and products).As a result of the pandemic, the digital space is so much more important than ever before. Therefore, to stay competitive, and to really understand the products from the consumer perspective, companies have to provide the most personalised customer experiences to acquire and retain their consumers. As Nicky mentions, ‘It is definitely worth making an ‘inventory’ to see how to promote what you have – it is about personalising the customer journey’.What are employers looking for in a Product Analytics candidate?Product Analytics are great due to their hybridity. In the current market, where there are numerous jobs, and few candidates, a Product Analyst (technically strong in three areas) is a highly sought-after rarity.Businesses are becoming increasingly invested in Product Analytics and having a Product team that works alongside the Digital team can be beneficial; especially when companies need to stay competitive.What are Candidates looking for? Understanding the differences between a Digital Analyst, and a Product Analyst is key to understanding what a candidate is looking for. Nicky suggested that this Product Analyst role enabled her to be the ‘bridge’ between areas.So how does the future of a Product Analyst differ to that of the route of a Digital Analyst? For Nicky, this is one of the most important factors to being a Digital Analyst, as she has the option to go down the Data Science route in the future should she wish. The more technical skills she has as a Product Analyst means she is building up experience across different areas of Data & Analytics, giving her a slightly different career path, should she want to go down a more technical route.Why Choose A Product Analyst Role?“If you come from a technical background – maths, physics, computer science – and are interested in how the numbers are crunching, it is worth going into Product Analytics, as it needs a logical mathematics brain, to be able to convert it into a way which is useful to stakeholders.”From speaking to Nicky, it is clear that Product Analytics is an up-and-coming role that people don’t know enough about it. Therefore, if you are curious about Product Analytics, or any of the different roles the market has to offer at the moment, as an employer looking for help hiring, or a candidate actively or passively looking for work, Harnham can help. Take a look at our latest Product Analytics jobs, or get in touch for more information on how we can support your hiring needs.
As Incidents Of Cybercrime Increase, How Can A Fraud Analyst Give Your Business Peace Of Mind?
Whilst it’s true that cybercriminals are becoming more creative and sophisticated, as are analytical techniques and the experts that wield them. Fraud Analysts now have more techniques and reach than ever, and as incidents of cybercrime increase, this isn’t an area that businesses should be scrimping on.
According to PwC’s Global Economic Crime and Fraud Survey 2022, 46 per cent of organisations surveyed reported experiencing fraud or financial crime over the last 24 months and tech, media and telecommunications businesses appeared to have taken the brunt. Findings showed that nearly two-thirds of this group experienced some form of fraud, the highest incidence of any industry.
The ONS also recently released stats showing that fraud offences increased by 25 per cent in 2021 (to 4.5 million offences) compared with the year ending March 2020. Indeed, the proportion of these incidents that were cyber-related increased to 61 per cent up from 53 per cent.
The rise of cyber-fraud is a clear issue and for some businesses such as financial institutions, tackling this by using fraud teams made up of expert Fraud Analysts is the norm. But for others, it may not have been seen as a priority until recently. However, any business which has a growing number of online transactions will become a bigger target for fraudsters and would benefit from a team member able to help minimise the risk.
So, how can fraud analysts help?
Far from wanting to paint a bleak picture, while fraud techniques are evolving and improving, so are anti-fraud efforts. All risks associated with financial crime involve three kinds of countermeasures: identifying and authenticating the customer, monitoring and detecting transaction and behavioural anomalies, and responding to mitigate risks and issues. All of these are carried out by fraud experts, such as Fraud Analysts, armed with ever-evolving technologies and techniques. So, what exactly does a Fraud Analyst do?
Fraud Analysts will track and monitor transactions and activity, identify and trace any suspicious or high-risk transactions, determine if there is improper activity involved, and identify if there is any risk to the organisation or its customers. They are able to digest huge swathes of information and quickly and efficiently prioritise the data that’s important in order to tell a story of fraud or no fraud.
To cope with the speed and scale of online commerce, new technologies such as Machine learning (ML) models have come to the fore. These models have the ability to simulate thousands of scenarios and take over the mundane tasks of sifting through swathes of data in a tiny percentage of the time it would take a human. The systems used by Fraud Analysts will vary based on the industry, but a common example is rule-based expert systems (RBESSs). A very simple implementation of artificial intelligence (AI) RBESSs are used to detect fraud by calculating a risk score based on users’ behaviours, such as repeated log-in attempts or ‘too-quick-for-being-human’ operations. Based on the risk score, the rules deliver a final decision on each analysed transaction, therefore blocking it, accepting it, or putting it on hold for analyst’s revision. The rules can be easily updated over time, or new rules can be inserted following specific needs to address new threats.
This method has proved very effective in mitigating fraud risks and discovering well-known fraud patterns. That said, rule-based fraud detection solutions have demonstrated that they can’t always keep pace with the increasingly sophisticated techniques adopted by fraudsters, without regular updates and expert use.
Machines also cannot mimic human traits like intuition. People can detect if things aren’t right even if they have not seen them before. It’s an instinct not yet successfully trained into machines. Therefore, new trends are much better pursued by an analyst and then a machine can be trained to stop future occurrences. A well-implemented ML system will free up precious time for an analyst to perform these more productive tasks.
A non-stop process
So, your Fraud Analyst has now set up a new ML system to identify fraudulent activity and is also looking for new trends that fraudsters may be trying – now what? Fraud Analysts never sit still. Their job is not a one-time fix but one of constant evolution and refinement. Their role involves identifying weaknesses in systems and continually looking for opportunities for improvement, such as recommending anti-fraud processes to detect new patterns or new software tools to help with reporting. Their finger is always on the pulse of emerging developments and will ensure your company remains protected against current risks.
Not only is this aspect part of the job description, but it is also to some extent inherent to their nature. Fraud Analysts tend to be curious, have a strong attention to granular detail, as well as an inclination towards problem-solving. Leaving no stone unturned is part of their makeup. This analytical skillset will dig out any problems that are there – which will unfortunately then require you to fix them (sorry!) – but it is far better to be aware of any weaknesses now. The majority of companies only realise their shortcomings when it is already too late. Ultimately it is better to be safe than sorry.
A Fraud Analyst not only helps to protect businesses against creative cyber criminals but will also give owners reassurance as they look to grow and thrive unimpeded.
If you are looking for a complete recruitment solution across the breadth of Data & Analytics disciplines to build out a robust Data & Analytics function, get in touch with one of our expert consultants here.
Looking for a new role? Take a look at our latest Fraud Analyst jobs.
The Next Generation of Data Analysts | Harnham US Recruitment post
From coast to coast, a new breed of data analyst rises. No longer siloed and pigeon-holed into one specific area or another, today’s professional must be able to nuance actionable insights for better business predictions and performance. The evolving role of data analyst marries technical prowess and analytical skills with the soft skills of coaching and communication.Every organization from AdTech to FinTech to the Food and Beverage Industries, and every industry in between, depends on data. In fact, by 2020, IBM estimates the number of open positions in the U.S. for data professionals will increase to 2.7 million. Yet, the surge and the shortfall in analytics talent remains as data analyst recruitment efforts rise to the challenge.Broaden Your SkillSetWith high demand and short supply comes the opportunity to go beyond your comfort zone and expand your skillset. Add to that companies that may not have the budgets to cover their recruitment efforts and the data analyst skillset must expand to meet the demand. From technical to soft skills, below are a few things to keep in mind when crafting your resume or CV:Don’t shed the basics of analytical mainstays such as Excel, SQL, and SAS; enhance them with languages such as R and Python. Want to boost your chances to the top of the pile? Don’t forget next generation tools and platforms like Tableau, Domo, Adobe Analytics, and/or Snowplow.Be specific: Companies will be more interested in interviewing you if you can clearly outline why/what you have used different technology for.Keep this punchy, concise, and outline your in-put with said technologies.Outline projects you’ve worked on.Become a storyteller – communicate key insights more effectively with the power of data, visualization, and narrative. The ability to tell a story with data can translate across business functions and departments for a unified predictive or prescriptive analysis for more impact.Offer actionable Insights – put the power of actionable insights into decision makers’ hands with real life application explanations. Steward data responsibly. Data governance is now business critical and the new data analyst must be able to act with fiduciary responsibility to ensure data privacy. Data must be protected, standards must be followed, and trust must be maintained
I, Meet RobotThe blending of the physical and digital worlds through AI, Machine Learning, and IoT remain the frontrunners in technology through 2020. According to McKinsey’s Report Ten IT-enabled Business Trends for the Decade Ahead, the latest technologies shaping the current business world include automated knowledge work, the mobile platform, and the Cloud. Skillsets and experience within these three technologies are the next wave in the modern digital world and it’s the new breed of data analyst who can best rise to the challenge to fill the gaps.Not only will these three technologies make an impact, but the impetus of social platforms and their data will be a powerful contribution to business outcomes. This melding of the physical and digital worlds allows businesses to understand and implement the collected data in scenarios in real-time driving them forward to better reward.Your TurnIn this section, we ask our candidates and clients what we as recruiters can do to help you find the perfect fit. This is your chance to answer and ask questions as well as get creative in helping us improve our efforts in data analyst recruitment. Below are a few questions to get you started.What kind of cross-training programs might businesses and schools employ for future Data Analysts?What other backgrounds are we overlooking in our quest to for the next generation of data analyst as businesses seek to find and engage this most critical role within their data teams?What can we, as recruiters do to engage qualified candidates ready for their next role in the world of data and analytics?If you’re a data analyst ready to spread your wings, we may have a role for you, check out our current vacancies or contact us to learn more.For the East Coast and Mid-West teams please call 212-796-6070, or email email@example.com.For the West Coast team call 415-614-4999 or email firstname.lastname@example.org.
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