Case Studies: Data Science careers

Dr Kim Nilsson, Pivigo:

Kim is an Astrophysics PhD turned Entrepreneur. She is the CEO of Pivigo, an organisation focused on supporting analytical MScs and PhDs in their career transitions into data science roles. She is passionate about people, data and connecting the two.

Kim realised that, despite being a Hubble astronomer, academia was not for her.  She undertook an MBA and worked briefly in financial services before setting up her own company.  Pivigo helps researchers gain commercial experience that will help them into a data science career.

On the day she spoke, there were 4003 jobs on LinkedIn with the title ‘data scientist’.  A starting salary will be £35-£50k.  The different sectors include commerce, operations, consumer marketing, local government and charities.

Key skills include Python, R and Java.  You need to have curiosity and scepticism, and ability to communicate and some business awareness.  Your CV needs to show HOW you apply your data skills to problems.

Check out MOOCs on Coursera, competitions on Kaggle or create your own data challenge!

Dr Ana Costa e Silva, TIBCO:

Ana has 15 years experience with data, undergraduate studies in Business and a PhD in computer science (AI) from the Edinburgh University. She has previously been a manager economic statistician for the Statistics department of the Portuguese Central Bank and a researcher of the inner workings of the global stock market for Edinburgh Partners.

Ana’s company helps businesses understand their data and start to respect their customers.  Her data analysis helps to optimise pricing, check for fraud, re-route transport (eg container ships avoiding storms and finding available docking).  She helps the engineers in the company make their products look better (eg in oil and gas, optimising engineering tools, and in healthcare, getting sensors to call nurses when there are changes in patient data).  One client was a casino company, MGM Resorts, and they looked at historic data to see which punters had not yet lost too much money: these people were texted with offers at other entertainment places and then encouraged back, as data demonstrated that people who had not lost too much were more likely to come back and spend more money.

Dr Zach Izham, Hewlett Packard Enterprise

Zach has a PhD in Mechanical Engineering and after several roles in aero-engineering, is now responsible for designing, implementing and testing solutions for data analytics and machine learning for clients in insurance/ banking/automotive industries and also governmental agencies from a ‘data science’ perspective.

He talked about why he left academia, citing the main reason as being that it would not be possible to earn enough money.  He works for HPE where he helps businesses leverage their data to run a more efficient business.  Issues he encounters are where servers don’t talk to each other and he has to find solutions to problems.  He encourage attendees to be picky about the business they choose to work in and consider starting their own business.

He says that AI becomes Machine Learning when it is mainstream, such as the self-driving car.

Interesting courses include Andrew Lung’s Coursera course and you should check out SiliconMilkRoundabout (jobs fair for tech people).

Mathematics and Statistics Support Centre – Paid Positions Available

King’s will be launching a support centre for maths and stats in September 2014. This follows a pilot in May 2014. The centre will be based in the Maughan Library at the Strand campus and open 2-5pm each weekday afternoon.

The Centre will provide mathematics and statistics support for students who use these skills outside of a Mathematics Degree, and support will be offered on a one-to-one basis by postgraduate students. Training and supervision will be provided for tutors and this is an excellent opportunity to develop your tutoring skills and build experience.

We are looking to recruit 15 students to offer this support, each working one 3 hour shift per week. The centre will be open in term time and we are recruiting for the full academic year. You don’t have to be studying in a mathematical discipline, but do need A-level mathematics and to be highly numerate in either mathematics or statistics.


It is essential that you meet the following criteria:

  • A-level mathematics (or equivalent) and a high level of numeracy
  • have excellent teaching / tutoring skills
  • can demonstrate reliability and punctuality
  • are eligible to work in the UK
  • are available for at least one afternoon shift 2-5, Monday – Friday during King’s term-times
  • are available for a full day’s training on 6 October

Experience of tutoring in maths and / or stats is highly desirable and preference will be given to those with this experience – although training will be provided.

Payment will be made through Direct Temping, and at spinal point 20 on grade 4 – £12.81 per hour.

If you are interested and meet the criteria we’d really like to hear from you. To apply please contact by 14 September 2014, with one side of A4 paper detailing:

  • your experience
  • your areas of expertise in Maths / stats
  • how you meet the criteria
  • your availability in terms of afternoons
  • confirmation that you will be able to attend a full day training session on 6 October.

NERC Postgraduate and Professional Skills Development Courses for 2013/2014

NERC is pleased to announce that the new e-brochure for the Postgraduate and Professional Skills Development Courses 2013/2014 is now available to download from our website: This includes full details of the courses and information on how to apply.

The courses are aimed at PhD students and early career researchers in environmental sciences. They cover a wide range of topics including statistics, modelling, bioinformatics, taxonomy and fieldwork techniques.

Funded places are available and will be allocated to NERC-funded PhD students and early career researchers as a priority. However, if sufficient places are available, other individuals may be eligible to attend.

Understanding Uncertainty in Environmental Modelling


Workshop for early-career researchers (PhD students, postdocs) in environmental modelling and simulation disciplines.

This workshop presents an overview of key stages in the modelling process: development, evaluation, practical use, and communication of results. Interactive discussion sessions and exercises will help participants explore concepts presented in the lectures and relate these to their own research. Themes include:

• Evaluating model performance;
• Statistical inference from ensembles of models;
• Why good statistics is not enough;
• What do decision-­‐makers want? What can environmental modellers provide?
• Effective dissemination of uncertain forecasts.

Speakers include: Leonard Smith, David Stainforth, Emma Suckling, Erica Thompson, Elizabeth Stephens (Reading), Lindsay Lee (Leeds).

See website for further details and to apply for a place:

Deadline for applications: November 15th 2013

This workshop is part of the NERC Postgraduate and Professional Skills Development Programme. NERC-­funded applicants will be given priority, but the workshop is open (and free) to all.

One PhD’s decision-making and success story, continued

Update from my last blog post in May of this year:


As I said in my last post I got through to the first Civil Service Fast Stream Statistician Assessment Centre.  This was pretty tough but they were purely testing your ability to analyse, collect data and disseminate information.  It consisted of about a day’s worth of tasks.  In between each task you sit with the rest of the candidates in the common room where everyone is in the same boat as you.  There are quite a few people so I found I ended up talking with the same 3-4 people throughout the day.  The detail that they provide in advance is pretty comprehensive, and I wouldn’t really have much more to add since I would imagine the tasks change, but here’s an example of a tough question from the interview:


Question: Write a regression equation (not difficult for maths student maybe but definitely for some whose background is psychology – I just know which buttons to press on the computer!).


My approach: I knew they were going to ask about regression because I indicated in advance that I knew about it.   I had more revised the rationale for using it and what it does rather than the underlying maths.  I just gave it my best guess and instead of writing the mathematical symbols just wrote words instead.  They seemed OK with that, and said to me, in quite a friendly tone, “Is it safe to say your background is social science?”


It can be a bit daunting sitting in the common room with people who have done Master’s degrees in statistics etc. but you have to comfortable with what you don’t know or what you can’t be expected to know, as much as what you do know.  They are very happy to accept applicants from social science backgrounds so I went into it thinking, “I’m not a mathematician, I can’t be expected to know these things” and I found this really kept me relaxed.  Moreover, don’t forget that people with maths backgrounds may be as strong on the data collection questions as those from the social science.


The day is pretty intense (10.30am-5pm and I never had more than 15 minutes of break but I think that may be because they were running behind).  You just have to keep going: I got a good night of sleep before had a good breakfast and a couple of cups of tea/coffee when I could!  In terms of task preparation, the day is all about statistics (with exception of one written task for which you can’t really prepare) so revise your basic stats, maths and data collection knowledge – especially the things you indicated you knew about in advance!


I was successful at this stage and was selected to attend the final assessment centre.  Personally, I found this day harder than the first, not least because it’s more like 8am-5pm.  The other reason I found it more difficult is that the first assessment centre tested your technical knowledge, whereas this one tests soft skills such as creative thinking and influencing people so it’s really difficult to gauge how you’re doing.


The second one is structured into a series of tasks testing different competencies and it’s best to approach it as though you’re at work.  There’s lots of writing, a group task, a presentation and an interview.  They give ample information about these and are really transparent about what they are testing and when.  All the assessors were really nice and there’s not an awful lot you can do to prepare, except brush up on the competencies being assessed in the interview (I found attending the Careers Service really helpful for this as they can run through a practice interview with you; the consultants have attended Fast Stream Assessment Centres so are very knowledgeable about the sort of questions that come up).


Unfortunately I wasn’t successful at this last assessment centre but one good outcome is that they are going to send me feedback.  I have my established ways of working and I just approached the whole thing event with my normal approach. If I were to do it again I wouldn’t change that, so I suspect it was just a lack of organisational ‘fit’, rather than a terrible performance on my part.


I had written off working for the Civil Service for the time being, when a couple of weeks ago they sent me an email offering me a position at the Home Office.  They have a system whereby if you are successful at the Statistician Assessment Centre but ultimately not offered a Fast Stream position you may be offered a Statistical Officer position (depending on your assessment centre mark), with no further assessment required.


I went to meet them recently at the Home Office and was really impressed.  Although the starting pay is a bit lower than the Fast Stream, your opportunities for progression are not impaired.  They say it might take a year or so longer to reach the grade 7 level (which is a grade everyone keeps talking about where your salary is about £40-45k).  Having said that, they acknowledged I have a PhD and were keen to stress that I should tell them if I get bored and that it may be possible to progress at the same rate as the Fast Stream.


The day job didn’t seem that different to what a Fast Streamer would do.  On the Fast Stream you’d be expected to move every 18 months or so and although there’s no imperative to do so in the position I’ve been offered it is still perfectly possible.  Indeed, they were very open about it.  The good thing about the Government Statistical Service (GSS) is that all the statistical staff in every department work for the GSS.  So you can move government departments (Home Office to Ministry of Defence for example) without moving from the organisation you work for and that means you can be quite open with your manager about your wishes.  So all in all, the main difference seemed to be the pay and that I suspect the Fast Streamers get a little more resource to develop themselves.  Also if you do get to this stage and you are very set on the Fast Stream you can always apply again from within the Civil Service; the people I spoke to were very happy to support that.


On an unrelated note, I have also been offered a position to stay at King’s to continue with research at a post-doctoral level for one year.  I’ve had some good results come out of my PhD and I’m lucky enough that my supervisor has some big projects on the go.  I’m just weighing up the pros and cons of each of my options now and trying to make a decision.

Byron Creese