Professionals with deep analytical knowledge, particularly using SAS, are in high demand. But to build a successful career, you first have to acquire the necessary analytical skills. Recently, I interviewed Andrea Baroni, a graduate from Lancaster University, and asked him to share his experience learning SAS and how it has helped advance his professional career.
Mayra Pedraza: Where did you grow up and how did you first develop an interest in analytics?
Andrea Baroni: I grew up in a medium-sized town near Milan, Italy. The strong international footprint of my bachelor studies in Economics and Business Administration at Universita’ Bocconi gave me chance to spend a semester as an exchange student in Universidad de Los Andes in Bogota, Colombia. This experience was my first encounter with analytics.
My first hands-on analytics experience was, in fact, a university course on “Data Mining for Direct Marketing and CRM.” I remember being amazed by the extent of augmented analytical capabilities allowed by the combination of human intelligence, statistics and software. (SAS Enterprise Miner was the main tool used during that course.)
I knew in that moment that I wanted to be part of the thrilling field of analytics, and immediately started looking for opportunities to get involved. In the year that followed, I attended courses on SQL and VBA, got my hands dirty working on data mining projects in SAS, SPSS, Knime and Microsoft Azure ML and participated in events such as the “Big Data & IoT Food Hackaton,” organised by Microsoft, where my team was awarded winner in the “Data Visualisation” Category. I felt like this was the right direction for me, but I still lacked hard skills such as programming, hence looked out for a highly analytical MSc course.
MP: What made you choose the Lancaster MSc degree course?
AB: The MSc in Management Science and Marketing Analytics was a perfect match to my ambitions given that its approach is focused on the development of highly analytical skills and, more importantly, on how these can be applied in business to support decision making, both from an operational and marketing perspective.
The prestige of Lancaster University Management School in the field of operational research and forecasting represented an additional incentive to apply. Not only did it give me the chance of attending courses delivered by members of the LCF, Europe's leading centre for forecasting research, but I also had the honour of being supervised by its Director and Co-Founder – Distinguished Professor R. Fildes – during my summer internship at BT Openreach.
MP: What did you like best about your course?
AB: In hindsight, the greatest added value of the MSc in Management Science and Marketing Analytics have been the fast-paced, deadline dictated work environment, the extended portfolio of programming languages and software (R, VBA, SAS, C++) taught and the great connections with industry. These often provide students with an eased access to a variety of summer company projects. The partnership with SAS plays a very important role as well, since the software is made available for modules like SAS Programming and Data Mining. All in all, I feel the skills gained during my course are highly sought-after in today’s job market and are likely to be even more in demand in the years to come.
MP: What did you find the most challenging on your course?
AB: As previously mentioned, the MSc constantly exposes students to tight, often multiple, deadlines. Although this might – and probably will – look unattractive to prospect students, it eventually provides a great training ground for professionals-to-be. In fact, I have found myself in similar situations – which my previous experience at Lancaster helped me to successfully manage – since my first day on the job.
MP: Where do you work and what is your role? Do SAS Analytics skills help you to find your job?
AB: I am now a Data Analyst at REaD Group. Our business is built around data; in fact, we own the most comprehensive collection of consumer data in the UK, which we sell and use to help our clients achieve higher levels of engagement with their customers. Knowing how to programme in SAS helped me to get the job in the first place, as it is the main software used by the Analytics & Insight Team. Similarly, our clients often require our analyses to be carried out in SAS so that they can integrate our models with their SAS Scripts at the end of the project.
MP: What’s your job like? Is there a normal day or is each day different?
AB: I know this may sound quite stereotypical but, in all truth, no two days have been the same since I joined REaD Group in October 2016. This is firstly because, as part of the Analytics & Insight team, I am exposed to an impressive turnover of projects which leads to new challenges and clients on a regular basis. In addition, we are urged to use a variety of methods and build models that are bespoke to the needs of our clients. This contributes to a great deal of learning and continuous mental stimulus.
Your projects and SAS®
MP: Can you give us brief idea of the projects you work on?
AB: The projects I have worked on since joining REaD Group include customer profiling, predictive models for repeated purchase and churn, forecasting, market segmentation and creation of automated reports both for clients and internal use.
MP: What are the benefits of using SAS for analytics?
AB: In my experience, the main advantages of using SAS in analytics are the ease of scale, the support provided by the supplier and the software degree of diffusion. SAS programmes can be easily integrated within different departments, regardless of the scale of the organisation, to exchange data and extract valuable information in real time. The support provided by the SAS team facilitates a sound implementation of the software throughout the business and represents a guarantee that any future issues will be dealt with rapidly. Finally, for a company like REaD Group offering consultancy services, SAS is often a deal-clinching selling point as clients see it as a synonym of excellence and are willing to use our scripts to repeat similar analyses in the future.
MP: Tell us about your experience using SAS in the context of marketing analytics?
I have used SAS for a variety of purposes within marketing analytics, both for university projects and in industry. In my opinion, SAS is a great facilitator for extracting insight from data, communicating them to stakeholders – both internal and external to the business – and speeding up decision making. During my experience as a forecasting analyst intern at BT Openreach, SAS was key to quickly be up to speed with the analyses conducted by the Forecasting Team before I joined, enabling me to build on their work instead of starting from scratch.
On a different note, I would like to add a note on how SAS Enterprise Miner can be used by anybody with a statistical background to build complex models in a very intuitive way. In fact, I see SAS EM as an ideal “first step” towards data mining, which can help students assess their interests and potentially steer their learning path in the direction of analytics.
MP: What do you enjoy doing in your spare time?
AB: I mostly enjoy outdoor sports and going out with friends in my spare time. I regularly run, play tennis and football, however my true passions are skiing, snowboarding and kitesurfing, which I have the fortune of practicing almost every year. I am also a big fan of networking events, which are an opportunity to learn more about industry trends, share knowledge and meet new people. Finally, probably due to my Italian origins, I enjoy cooking for my family and friends – but not as much as eating in a good restaurant!
MP: Do you consider yourself as a Data Scientist? From your experience, what do you think are the characteristics that a data scientist needs in today’s job market?
AB: A few weeks ago I was asked a similar question by the Head of Data and Analytics at a large media corporation. Due to what is probably a professional bias (alias “geekiness”), I replied with a gap analysis between my current skill set – prevalently business- and marketing analytics-led – and data science. My interlocutor giggled at me and said: “Well, you may not have studied data science, but as long as you can talk about it as you are doing now and use data to tell a story, you definitely fall in this category in my opinion.”
I think his words held some truth in that data science is a relatively recent field that is still evolving. This clearly varies between industries – it does not come as a surprise that a PhD is often required for analytical roles in companies like Google or Facebook – however, I believe the key traits of a data scientist are:
- Rock-hard analytical, communication and team-working skills.
- Solid knowledge of at least one programming language (e.g. SAS, R, Python).
- Experience handling big datasets (SQL) and extracting insight from them.
- Practical, business-led approach to problem solving: programming can be fun, however excellent is the data scientist who envisions a solution both profitable and suitable to the company’s strategy.
Finally, regardless of the role, employers look for evidence of proactivity and experiences that make the candidate stand out from the crowd of “standardised CVs” that they receive every day (or, to put this in statistical terms, for “outliers”). This demonstrates ambition and eagerness to learn, which are often predictors of good performance after employment.
MP: Do you have any advice for students who are interested in the field of analytics?
AB: There hasn’t been a better time for students with interests like yours: analytics skills are and will be in increasingly high demand. Make sure you make the most of your time getting your hands dirty and learning the basics of analytics. Do not be scared by the endless options available in terms of software, languages and techniques today available; what eventually matters the most is the approach and ability to learn and adapt to change. Do some research on the tools used in industry, pick one to begin with and then play it by the ear based on the opportunities and experiences you will be presented with – or, ideally, you will proactively seek. There is no such thing as a “useless experience” as they will all pay off both at a recruitment stage and on the job.