Insight Analytics Manager
Bristol / £55000 - £60000
£55000 - £60000
UP TO £60,000 + BENEFITS
Harnham is working exclusively with a FTSE 100 company on an Insight Manager position. You will be joining their Insight & Analytics team at a time when the business is becoming increasingly data led. This is an influential role that works with teams across the organisation to leverage insight that enables intelligent decision-making and strengthens the organisation`s understanding of the world in which they operate.
- Support the senior leadership in the assessment of the changing external business environment and the identification of opportunities and threats
- Develop, communicate and promote a consistent and forward-looking view of the market
- Generate meaningful insight and recommendations to inform operational decision-making and strategic plans (including growth opportunities) through the co-ordination of data collection, analysis and research.
- Produce meaningful dashboards on the market that draw out key insights and support business decision making
- Build a hub for market knowledge and understanding of broader sector trends
- Manage an Analyst and analyse large amounts of financial and customer datasets through SQL
We would like to hear from you if you tick any of the following criteria:
- Experience and evidence of adding business value through trend analysis, analysing data and generating insight
- Highly numerate and analytical with the ability to connect various data sources and derive meaning
- Coding skills in SQL as well as some sort of visualisation tool ideally Tableau
- Strong articulator with the proven ability to interact, consult with and professionally influence senior management.
- Ability to tell a story through data and communicate trend analysis in an innovative and engaging manner
- Strong planning and prioritisation experience with a focus on project delivery
- Strong IT, data visualisation and analytics systems skills including Microsoft Office (especially MS Excel, tableau or equivalent)
You will receive:
- Up to £60,000
- An annual bonus
- Flexible working
- And more!
How to apply
Please apply by submitting your CV to Emma Johnson at Harnham.
How Advanced Analytics and Customer Engagement Create Insight for Your Business | Harnham US Recruitment post
Have you ever wondered why your favorite store stopped carrying an item you liked to purchase? Or how you discovered a new item to fit the bill for what you were searching for? Consider counterintuitive holidays where the stores are packed, but the checkout lanes are light with few cashiers. On the flip side, there may be opportunities in stores that have ensured they have plenty of product in stock, have extra staff to help, and through it all have managed to make the experience seamless.This last imagining is what happens when you bring Advanced Analytics into your business to gather insights and create customer engagement for people who will return again and again to your store and to buy your product. This isn’t just for brick-and-mortar stores, this includes digital and e-commerce businesses as well. But the big question here is, how did they know to hire extra staff, make sure there was enough product on hand, and not only retained former customers, but made new customers? The motto ‘know your customers’ holds true, even in, and especially in, today’s world of social media marketing, e-commerce shops, review opportunities, and more. Enter Advanced Analytics. The next step up from the Analytics of Business Intelligence to offer you and your business a birds-eye view of what your customers want, how they want it, and how you can ensure their experience keeps them returning, and opening doors to new customers as well. TRADITIONAL BUSINESS INTELLIGENCE (BI) VS ADVANCED ANALYTICS Business Intelligence gives historical performance Data. What have customers bought or thought in the past. This information has been used to inform how to improve processes now, for the next sale, call, or booking. Advanced Analytics, however, offers not only a system in which to capture historical Data, but can work with more complicated systems, and handle the massive amounts of Data businesses capture every day. Think of Advanced Analytics as the change agent who comes in to solve the more complicated issues. While it may still gather the same information, it will use the information to determine why something is working, and if something isn’t working, what is the root cause of the problem. If customers are returning again and again, what is bringing them back, and how can they repeat it and improve it for the future. Below are three types of analytics each with its own specialty to help you make more informed decisions to move your business forward. 4 BUSINESS OPERATIONS ADVANCED ANALYTICS SHINESGaining clear insights about your business involves more than just the experiences of your customers. The driving force behind happy customers are the operations of your business. From the supply chain to marketing to Human Resources, every department plays a role in the Customer Experience. So, what better way to use Advanced Analytics than to ensure the root of your business is running well which will be key to ensuring that smooth customer experience. · SUPPLY CHAIN ANALYTICS – Market demand is at an all-time high and supply is…well, it’s stuck a bit. But regardless of what’s being moved, where, and how, the remote workforce, globalization, and necessary manufacturing plants to handle the loads are making things more complicated than ever before. Advanced Analytics can help businesses plan for what will be in demand not only using past performance indicators, but also predictive modelling scenarios to try to meet the pain points of supply and logistics.· OPERATIONAL ANALYTICS – Changing market demands, adaptable processes, and flexibility in how operations are executed are all signs Advanced Analytics ha a place at the very heart of your organization. In this scenario, bits of seemingly unconnected Data come together to help imagine process alignment with market demand, and craft better insights for business.· RISK ANALYSIS – Cloud-based tools available to help identify management of massive amounts of Data with predictive insights using Advanced Analytics.· HUMAN RESOURCE ANALYTICS – To find and retain top talent, it’s important to ensure your business knows what they need, why they need it, and who can meet their requirements. Advanced Analytics can offer HR the chance to predict and evaluate how a prospective employee may do in your organization. Ready to take the next step in getting a birds-eye view of your business? Consider Advanced Analytics. Imagine knowing not only the historical Data which has kept your business moving forward, but using the near real-time Data streams from omnichannel sources to help you plan for the future of your business with future-predictive insights. If you’re interested in Digital Analytics roles, a career in Advanced Analytics, Machine Learning or Robotics just to name a few, Harnham may have a role for you. 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 firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
How to Break into the Data Industry: Career Advice from Analytics Manager Simon Kelly
The Data and Analytics market is growing rapidly.
By 2030, the global market size for Data and Analytics is projected to reach £266 billion, a CAGR of nearly 30%. This increasing popularity has made the Data and Analytics space extremely competitive and difficult to break into.
Because of this, one of our consultants, Emma Johnson, spoke with hiring manager Simon Kelly to learn how they managed to navigate through this extremely competitive field when they first started.
Kelly is an Analytics Manager who works at Entain, and has been in Data & Analytics since 2011. Kelly has had a very successful career working within Credit Risk, Finance, and now Gambling. Here’s a summary of Kelly and Johnson’s discussion, along with some key insights from their conversation.
Background on Simon Kelly
Q: How did you get into Data and Analytics?
A: After University, I went travelling the world for the most part of a year. Before travelling I went back home and worked in a call centre at Capital One as I knew people there and knew it was a reputable company. After travelling, I joined Capital One again and started in Operations and quickly worked my way up.
It got to the point where with my degree and my background in being naturally good at maths, it meant I was getting more involved with Excel in building reports and working with the analysts. So, I spoke with my boss at the time, who was great, and they created a role for me. This role was a junior analyst role but in between Operations and Analytics, and gradually I was doing more hardcore analytics stuff, including data analyst type (forecasting/controls & MI report building) tasks and more strategy, and it built from there.
Insight #1: You don’t need a technical degree to get into data analytics
Q: What did you study at university?
A: I started off in Mining Engineering which involved a lot of Physics, Chemistry and Maths. After studying this for a year I realised this wasn’t quite the right fit and then moved to Accounting and Finance.
Shortly after the change, I realised I wanted to open it up into business more generally as I wasn’t sure that I wanted to be an accountant or to limit future career opportunities. So, I ended up with a business degree but there were still lots of elements of economics and accountancy in that too.
Insight #2: What you do need, is a love for problem-solving
Q: What has kept you in Data & Analytics?
A: I guess quite simply like just being able to understand things and the problem-solving aspect is very rewarding. Data is usually the way to at least get some insight into things within a business and then you can brainstorm and talk to others and figure out what’s really happening. But data is the key to unlocking that and there’s often so much variety within that as well. Sometimes it’s challenging to get what you want out of the data, but once you do it usually makes sense, or it is it’s a starting point, something that you can focus on and then bring in other information to figure out what’s going on.
Insight #3: Data without context is useless
Q: What’s the most important advice would you tell your younger self?
A: I guess the key thing is when we think about data, data in isolation isn’t very valuable. You need to understand the context of it. You could be a great coder but if you can’t say what the insight is, (the ‘so what’) i.e. what does that mean to the business/customer then the data in itself is only so valuable. Do that storytelling and understand it in the business and customer context, without that there’s only so far you can go with purely just data.
Insight #4: When interviewing for a role. don’t hold back on your answers – hiring managers want to hear your thought process
Q: What advice would you give to candidates interviewing?
A: Don’t hold back. I think sometimes we push to try to get insight from candidates because we think they know it. But maybe they are reluctant to just go out there and say it for fear of saying the wrong answer. A lot of the time we’re not necessarily looking for the right answers. It’s more on the critical thinking and point of view of how they got to the answer.
So, if we ask a question, you’re not sure about, then take us through your thought process explaining bit by bit. And if it’s to go down a path and it’s not quite on track with what we’re looking for, it doesn’t give us enough to get a gauge of your thought process, we’ll ask you a slightly different question to try to bring you back on track. As a hiring manager, understanding this whole process and how a candidate got to an answer, even if it’s completely different to what we expect is way, way better than just saying, oh, I’m not sure.
Insight #5: Data skills are transferable across different industries
Q: What made you make the change from Credit Risk/Finance to working with Gambling?
A: The change of industry was quite natural because even though I was in credit risk and finance, it was more Consumer Finance – Collections and Recoveries. So, trying to understand people/customers and their financial situation and how can the Creditors help them identify them, segment them, and help them.
In a similar lens what we do in Safer Gambling is the same sort of thing. Trying to identify people who we should be protecting more. Using data to understand a customer’s affordability. Are we doing things correctly and for the benefit of the business and customer? It’s quite similar in that sense. It’s just identifying and understanding that customer using data and helping make the situation better.
Insight #6: You don’t need to know exactly where you’re going next
Q: Where do you see yourself in 5 – 10 years’ time?
A: I’m really enjoying Entain and my role at the moment but longer term, I’m not solely set on one industry or one company or anything like that, so who knows? I want to ensure there’s progression, that I’m enjoying the role that I’m doing, and that it’s a nice balance of challenging and rewarding – then I’ll continue to be happy. There’s no title that I’m aiming for anything like that, I just want a fulfilling and varied role where I can make a difference and slowly continue to progress from a career point of view.
Are you a data professional that’s looking to make a career change, or break into the industry? Get in touch today.
Keepers of the Data Kingdom: the Analytics Engineer | Harnham US Recruitment post
If it seems the Data world is drilling down further into niche specialities, you’re right. Considering the swathes of information sent and received on a day-by-day, minute-by-minute, and second-by-second basis, is it any wonder? The sheer volume, depending on your business and what you want to know, requires not just a Data team, but must now include someone with a particular skillset, including the tech-savvy analyst who can speak to the executive team.So, who holds it all together? These swathes of information. Who organizes the information in a cohesive order, so anyone with a map, can make their own analyses? Enter the Analytics Engineer.What Makes an Analytics Engineer an Analytics Engineer?Though it’s a rather new speciality within the Data Scientist scope—think Machine Learning Engineer, Software Engineer, Business Analyst, etc—at its core, the definition of an Analytics Engineer is this: “The analytics engineer sits at the intersection of the skill sets of data scientists, analysts, and data engineers. They bring a formal and rigorous software engineering practice to the efforts of analysts and data scientists, and they bring an analytical and business-outcomes mindset to the efforts of data engineering.” Michael Kaminsky, consultant, and former Director of Analytics at Harry’s.In other words, analytics engineers, using best software engineering practices transform data through testing and documentation so that data analysts begin with cleaner data to analyze. As technically savvy as the engineer must be, they must also be able to explain to stakeholders what they’re looking at so they can formulate their own insights. Five Roles and Responsibilities of the Analytics EngineerLike all new niche specialities, there are core responsibilities to consider as well as that of skillsets required to either study to become an Analytics Engineer or to discover if you’re one already. How? Consider the questions you ask, your studies within Data Science, Computer Science, Statistics, and Math, and your balance between technical skills and soft skills. Below are five things to consider when thinking about this role:Programming language experience. Experience with programming languages like R and Python along with strong SQL skills which are at the core of this role. DBT technology knowledge. As the driving force behind the rise of Analytics Engineer as a separate role, it’s imperative anyone interested in pursuing it should have a firm grasp of DBT — the Data Build Tool — that allows the implementation of analytics code using SQL. Data tracking expertise using Git. Data modelling. Clean, tested, and raw data which allow executives and analysts to view their Data, understand it within the database or its warehouse. Data transformation. Analytics Engineers determine what Data is most useful and transform it to ensure it fits related tasks. It’s part of building the foundational layer so businesses can answer their own questions. Key Changes Leading to the Shift in Data RolesWith every technological advancement their comes new players to the field. The difference is here is that the job description already existed. We were only missing a title. But from the traditional Data team to the modern Data team, there are a few key changes that point directly to the rise of this niche field. Cloud warehouses (like Snowflake, Redshift, BigQuery) and the arrival of the DBT the foundational layer which can be built on top of modern data warehouses are the first two that come to mind. Then, the Software-as-a-Service (SaaS) tools like Stitch and Hevo are capable of integrating Data from a variety of sources, and the introduction of tools like Mode and Looker allows anyone interested in drawing insight from Data to do so on their own.Who Needs an Analytics Engineer? Small or Large Businesses?The short answer is it depends. But the general rule follows that while both large and small companies can benefit from having this professional on their staff, there are different things to consider. For example, a small business may be able to find what they need in a single individual. The Analytics Engineer is something of a jack-of-all-trades. Larger businesses, on the other hand, may already have a Data team in place. In this case, an Analytics Engineer adds to your team, something like an additional set of eyes increasing insight drawn from those large swathes of Data we spoke about earlier.So, what’s next for the role of Analytics Engineer? Who knows? The roles of any Data industry professional is constantly evolving. If you’re interested in Analytics Engineering, Machine Learning, Data Science, or Business Intelligence just to name a few, Harnham may have a role for you. Check out our latest Data & Analytics Engineering jobs 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 firstname.lastname@example.org. For our Arizona Team, contact us at (602) 562 7011 or send an email to email@example.com. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to firstname.lastname@example.org.
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