Careers: LexisNexis Risk Solutions Australia modelling team

The Australian modelling team began as a consulting, software, and analytics firm established in 1999. We became an internationally recognised leader in customer modelling and insurance price optimisation software.

Since 2008 we have been an integral component of LexisNexis Risk Solutions, a leader in helping business make smarter decisions through information and technology. We take the best of both worlds; retaining our nimble consulting heritage alongside the financial and market security of a larger parent.

Our offer:

  • Opportunity to apply your technical skills in a consulting environment
  • Outstanding growth potential in a small team environment with an international reach
  • Work alongside clients on high profile, collaborative engagements
  • An exceptional salary

Job description:

  • Consulting: work closely with clients to assess existing systems, propose & implement solutions, train in our processes and present results
  • Analysis: build, manage and utilise statistical models & relational databases
  • Development: create new and enhance existing tools
  • International travel: a few 2-3 week trips a year

Targeted Disciplines:

  • Maths, Statistics, Operations Research, Science, Engineering, Econometrics, Actuarial


Career path

Start off as a generalist...

  • Work on client engagements delivering project components and training clients
  • Assist in developing new features for the software suite
  • Craft and deliver presentations
  • Construct models to identify value from various data sources
  • etc...

...where to from there?

 

  • Stay a generalist but take more responsibility; Senior consultant, manager, director
  • Or specialise… e.g. modelling, software, or client delivery
  • Or something completely different within LexisNexis

Consultant

A typical workday

8.30 am: Catching up with emails. We have several clients in the US and UK who are currently using the software, and every so often they run into trouble & need our help. A client I haven't talked to a while has emailed to ask about some elasticity numbers he's seeing and why they're so low. I write an email outlining things that could be going wrong, and suggest we line up a call if none of my suggestions work.

9.30 am: stand-up meeting to discuss upcoming work for the week. For me, this week's priorities are preparing for an upcoming client site visit and facilitating an upcoming release of our software.

10 am: We're overhauling the way that users create and run simulations in our software, and we had a meeting last week to bounce around a few ideas. Now I'm going to consolidate the results of that meeting into a spec for the new feature.

11 am: I'm working on a model using credit data to predict claims for our UK data business. I've finally wrangled the data into something sensible to model with: today I'll begin modelling proper, trying to find some extra predictive value from customer credit data.

12 pm: Lunch. Maybe Mexican, if I can stand the whinging from everyone who's gone to the USA about how inferior all the Mexican food here is.

1 pm: I start work on the slides for my upcoming trip. I'll be giving a presentation to the client team on how to use our software, which I'm finishing off.

3 pm: I'll need a demo for my trip too: a script to follow to show off our software. I find the last one we used and change it to suit this client's needs.

4 pm: Meeting over the phone with the client team to discuss their progress and offer support. They give us a status update on some new price test data that they're assembling, and ask us for some help selling their results to their product managers. We give some advice and offer to come up with some simple charts, which have proved effective in the past.

5 pm: A meeting with the consultants and developers about the simulator redesign. We discuss the general schedule for the changes, and the documentation I put together earlier.

Senior Consultant

A typical workday

8 am: One of my colleagues, Mark, is currently onsite with a client in the UK, helping them to design optimised prices for their home insurance business. I call him to discuss what progress they have made and what we can help out with in Melbourne today. He tells me they having been seeing some unusual looking results and we brainstorm possible causes. We agree that we in the Melbourne office will dig into this further to hopefully have a more concrete answer on the cause for him to work on tomorrow.

9 am: Weekly status meeting to discuss progress implementing a new software feature to allow users to build models more quickly. The developers are making good progress but have some questions about how clients will use the tool. We agree we are still on schedule to have the tool ready for release in three weeks' time and that we should begin more thorough testing, using the tool as it will really be used.

9.30 am: A few of us go to get a coffee. Use the opportunity to pick some brains about the issues Mark is having.

10 am: Have a meeting with Tom, a consultant, to discuss how we can help with Mark's problem. After further thought, a data problem seems more likely. I ask Tom to dig in to where exactly the problem could be. We agree to talk again at 3.

11 am: Bruce, a senior manager, has asked me to prepare some slides for a meeting he has next week, pitching a new product to an existing client. I start with pen & paper, first deciding on high level points, then those below them. After a lot of reordering and scribbling out, I get something that I think works. Summarise it in an email & send it to Bruce for him to review.

12 pm: A bunch of us head to lunch together at a nearby café. Conversation turns to the latest smartphone Nokia has just announced which revives the old Apple vs. Android vs. Windows phone discussion again.

1.30 pm: Catch up with Bruce to discuss where my thinking is at re: the slides he asked for. He suggests a different way to arrange the argument in one of my key points. Generally he thinks I need to emphasise more why this product will be an improvement on the client's current practices. He also says he will need an appendix that goes in to some of the more technical details.

3 pm: Time to see how Tom has gone digging in to the data. He thinks he has found the cause of the problem (or at least one of the causes). We now have enough of a lead for Mark & the client to follow up on today.

3.30 pm: Finally catch up on all the emails I have been ignoring so far today. There is a draft of document Ben, another consultant, has written to summarise the outcome of some R&D he has been doing – put that aside to read on the train tonight. Also a question from a client asking how they can get the numbers they need for an internal presentation out of our software – I ask Tom to have a go at writing a response.

4 pm: Start putting together the slides for Bruce's deck. I know there are some from other presentations that I can more or less reuse. Others will take more work. On the comparison of the benefits our new product provides over the client's status quo, I need to come up with a chart or two that quickly and intuitively convey the difference. I'll need to plug some numbers in to the mockup we have put together to see how compelling different ways of quantifying the benefit look.

5 pm: Call with UK client. Explain to them and Mark what Tom found today. They agree that it doesn't make sense and will work with their data team to get to the bottom of it today.

How to apply

Interested in joining us?

We're seeking candidates who are...

  • Excellent communicators
  • Highly numerate with strong analytical skill
  • Pragmatic, avoid 'reinventing the wheel', and ready to learn new skills quickly
  • Self-motivated to work effectively with colleagues in a fast developing environment
  • Interested in as many as possible of: data analysis, business strategy, maths & stats, programming

If this sounds like the job for you, please send your CV, academic transcript, ENTER and cover letter to odt-recruit@lexisnexis.com.

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