Decision Science Jobs

What We Do

Every aspect of business now benefits from the efficiencies that the extrapolation of insights from analytics can deliver.

The collaborative approach of Decision Science teams helps the decision-making process achieve far superior results than ever before. Combining mathematical equations, tech and behavioural sciences for the most informative insights is now standard and has seen the industry progress at a rapid rate. 




We help you make the Right choice

The need to leverage and process the huge amounts of data gathered by a business each day in an unbiased manner is a difficult chore to a gain completive edge.

Harnham meets the needs of diverse brands who realise and understand that interpreting data intelligently can provide answers to solve complex business problems. We are the recruitment firm dedicated to provide decision makers with the staff to help them make the most informed decisions. 

Latest Jobs

Salary

400000kr - 500000kr per annum + BENEFITS

Location

Stockholm

Description

This opportunity offers you the chance to be a part of designing, implementing and monitoring Credit strategies using SAS or SQL.

Salary

400000kr - 500000kr per annum + BENEFITS

Location

Copenhagen, Copenhagen Municipality

Description

This opportunity gives you the chance to assist in the design, implementation, and monitoring of credit strategies whilst using SAS or SQL?

Salary

£50000 - £65000 per annum + Competitive Benefits

Location

London

Description

A senior decision science role offering end to end model development and a blend of statistics and machine learning in the credit scoring space

Salary

£30000 - £38000 per annum + competitive benefits package

Location

Birmingham, West Midlands

Description

This is a fantastic opportunity that will suit a self starter looking to be part of a leading (and growing) brand within its space.

Salary

£60000 - £70000 per annum + competitive benefits package

Location

London

Description

Lead Decision Science Analyst opportunity for a Credit Card business where you will also have 1 direct report!

Salary

£55000 - £70000 per annum + Competitive Benefits

Location

London

Description

A high profile fin-tech lender is seeking an experienced Analyst for a Profit Modelling role

Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out our recent posts below.

The fight for senior risk analysts

If you have had difficulties hiring a Senior Risk Analyst recently, and you’re scratching your head as to why – this article should hopefully shed some light on the matter. Year on year we have seen the demand for Senior Risk Analysts skyrocket, making them the most sought after analysts in the ever-evolving world of risk. It’s no surprise that since 2012, the growth of challenger banks and the subprime sector means hiring candidates with experience in risk/FS alongside experience of SAS, has become even more challenging.The growth in demand just can’t be matched by supply. Risk analysts with 2-5 years’ experience are the golden eggs within this rapidly growing and advancing market and it seems that everyone wants them. If a strong Senior Risk Analyst comes on the market, they can have as many as 15 roles to consider at any one time – now this is great for the candidate but it is a recruitment nightmare for the companies looking to get this person on board. I have seen the good, the bad and the ugly when it comes to recruitment processes and these 5 tips below will give you a huge advantage in securing your perfect candidate in the face of fierce competition!1. You must have a slick and efficient recruitment processThe days of a 3+ stage recruitment process for Senior Analysts are over. Why do three one-hour interviews when you can cover it all in one stage and send a message of intent to the candidate? If the recruitment process is slow, unorganised and laborious, a candidate will perceive that this is what it is like to work for the company. Ultimately, the quicker the process, the more chance you will have of securing your perfect candidate.2. Sell, sell, sellAt the end of the day, the purpose of an interview is for the candidate to show off their skills in front of a prospective employer. But as the interviewer, you have a duty to sell the role as much as possible because if you don’t, I can guarantee your competitors will. Another big sell is skipping any testing at the first stage – face-to-face interaction as a first stage is such a good way to get a candidate engaged in a process. Sometimes, there may be 2-3 stages before candidates have even met anyone in the company!3. It’s the little things that make a big differenceBelieve it or not, some people don’t like regular contact from recruiters requesting updates on their situation (I couldn’t believe it!). One really nice touch I have seen work is a hiring manager calling their preferred candidate from their personal mobile in between interviews to check in and see how things were going – little things like this can make a big difference in the long run, and only take a couple of minutes.4. Best offer firstThis is the most frustrating thing that I come across in recruitment. Companies sift through a huge number of CVs sent through by recruiters/direct applicants, spend countless hours interviewing candidates, and when they finally find the perfect candidate, they under-offer them to see whether they can get them slightly cheaper… It all comes back to intent, and by offering the best possible offer first time, it sends a positive and decisive message to any prospective candidates.5. Flexing on skills – have you considered it?Although it may not always be ideal to begin with, employers flexing on skills and experience is something I have seen work a number of times over the past 12 months. For example, a role may be open for 6 months whilst the employer is trying to find their perfect candidate but within that time, they could have hired someone who didn’t quite tick all of the boxes, trained them up in 3 months and saved themselves a lot of time and money! If you think the candidate can pick things up quickly, definitely consider them.It’s never going to be a seamless process when attempting to hire a Senior Risk Analyst so don’t make it harder for yourself!

Fighting Crime with Data: An Ethical Dilemma

Can you be guilty of a crime you’ve yet to commit? That’s the premise of Steven Spielberg’s 2002 sci-fi thriller ‘Minority Report’. But could it actually be closer to reality than you think.   As technology has advanced, law enforcement has had to adapt. With criminals utilising increasingly sophisticated methods to achieve their goals, our police forces have had to continuously evolve their approach in order to keep up.   New digital advances have refined crime-solving techniques to the point where they can even predict the likelihood of a specific crime occurring. But with our personal data at stake, where do we draw the line between privacy and public safety?  Caught on Camera   The digital transformation has led to many breakthroughs over the past few decades, originating with fingerprint analysis, through to the advanced Machine Learning models now used to tackle Fraud and analyse Credit Risk.   With an estimated one camera per every 14 individuals in the UK, CCTV coverage is particularly dense. And, with the introduction of AI technologies, their use in solving crimes is likely to increase even further.   IC Realtime’s Ella uses Computer Vision to analyse what is happening within a video. With the ability to recognise thousands of natural language queries, Ella can let users search footage for exactly what they’re after; from specific vehicles, to clothes of a certain colour. With only the quality of CCTV cameras holding it back, we’re likely to see technology like this become mainstream in the near future.   Some more widespread technologies, however, are already playing their part in solving crimes. Detectives are currently seeking audio recordings from an Amazon Echo thought to be active during an alleged murder. However, as with previous requests for encrypted phone data, debate continues around what duty tech companies have to their customer’s privacy.  Hotspots and Hunches Whilst Big Data has been used to help solve crime for a while, we’ve only seen it begin to play a preventive role over the past few years. By using Predictive Analytics tools such as HunchLab to counter crime, law enforcement services can:  Direct resources to crime hotspots where they are most needed.  Produce statistical evidence that can be shared with local and national-level politicians to help inform and shape policy.   Make informed requests for additional funding where necessary.   Research has shown that, in the UK, these tools have been able to predict crime around ten times more accurately than the police.   However, above and beyond the geographical and socioeconomic trends that define these predictions, advances in AI have progressed things even further.   Often, after a mass shooting, it is found that the perpetrators had spoken about their planned attack on social media. The size of the social landscape is far too big for authorities to monitor everyone, and often just scanning for keywords can be misleading. However, IBM’s Watson can understand the sentiment of a post. This huge leap forward could be the answer to the sincere, and fair, policing of social media that we’ve yet to see. Man vs Machine  Whilst our social media posts may be in the public domain, the question remains about how much of our data are we willing to share in the name of public safety.   There is no doubt that advances in technology have left us vulnerable to new types of crime, from major data breaches, to new ways of cheating the taxman. So, there is an argument to be had that we need to surrender some privacy in order to protect ourselves as well as others. But who do we trust with that data?  Humans are all susceptible to bias and AI inherits the biases of its creators. Take a program like Boulder, a Santa-esque prototype that analyses the behaviour of people in banks, determining who is ‘good’ and who is ‘bad’. Whilst it can learn signs of what to look for, it’s also making decisions based around how it’s been taught ‘bad’ people might look or act. As such, is it any more trustworthy than an experienced security guard?  If we ignore human bias, do we trust emotionless machines to make truly informed decisions? A study that applied Machine Learning to cases of bail found that the technology’s recommendations would have resulted in 50% less reoffenders than the original judges’ decisions. However, whilst the evidence suggests that this may be the way forward, it is unlikely that society will accept such an important, life-changing decision being made by a machine alone.  There is no black and white when it comes to how we use data to prevent and solve crime. As a society, we are continuously pushing the boundaries and determining how much technology should impact the way we govern ourselves. If you can balance ethics with the evolution of technology, we may have a role for you.   Take a look at our latest roles or contact one of our expert consultants to find out how we can help you. 

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