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Quantitative Analytics Jobs

The model candidate

We have seen this role evolve over time to the structure it now inhabits. 

Working with numerous financial firms, we have placed talented Quantitative Analysts who have grown with the industry, bringing a wealth of experience and formal mathematical concepts.

The quantifiable management of risk underlines the decision making of many financial institutions. Placing candidates who have extensive skills in computer programming languages such as C, C++, Java, R, MATLAB, Mathematica and Python is something we specialize in.

Though the competition for roles is tough. Quantitative Analytics is a vibrant and stimulating discipline, with varied responsibilities; touching on aspects of statistics and predictive modeling.

We are well versed in spotting the essential skills and attributes the right candidate possesses. Beyond being highly numerate, we understand that it is our candidates' varied backgrounds that make them more rounded through practical experience.

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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.

How Computer Vision Is Changing Healthcare

It may seem like every new decade we have a new technology to master. But what if we’ve flipped the script? Now AI has a new technology to master. I'm talking about Computer Vision. Just like humans learn to identify shapes into objects as children, so too, must the technologies we’ve created.  Why? Because autonomous vehicles need to know the difference between a tree and a person holding their grocery bags. Because manufacturing bots need to identify defective products before they go to the public. And in healthcare, Computer Vision can help us identify disease, help doctors make diagnoses, and dig deeper into what makes humans human. Three Trends to Watch  Already, systems have a 99% accuracy rate at emulating human sight. Like our own calculations when we “see” an object, machines will have to process, analyze, and understand the image as well. Thanks to Machine Learning and Neural Networks using pattern recognition, this is possible. What could this mean for the healthcare industry? Imaging Devices like X-Rays and MRI Machines will get smaller and more mobile. This trend will allow simpler imaging, quicker workflows, and live imaging for quicker diagnoses.Next Generation Phenotyping (NGP) allows predictive diagnoses using Computer Vision and Deep Learning to analyze data at the molecular level. Telemedicine to open greater access to your doctor rather than the traditional brick-and-mortar doctor’s office visit. Electronic Health Records (EHR) for a patient profile gives direct access to patient information and could reduce the cost of logistics and gaps in expertise. And Remote Patient Monitoring (RPM) allows for real-time medical decisions to flow between patient-doctor without the ubiquitous red tape traditional medicine brings. Recent advancements in visual technologies will have a strong impact in a variety of industries. But it’s in the healthcare industry, Computer Vision, AI, and IoT will particularly shine as the technologies converge for greater progress in healthcare.  AIoT and Image-Based Data Converge for Improved Outcomes  There are such a variety of uses for Computer Vision in medicine, it can be hard to imagine where it can't be used. When you consider how much medical data is image-based such as mammograms, MRIs, CT Scans, X-Rays, and Echocardiograms, it’s easy to see how patients will benefit.  Imagine getting an early diagnosis to stop the spread of cancer or stopping dementia in its tracks. These systems alone can assist with surgery, identify problems early, and more. When your medical team of institutions, providers, and patients have access to these systems and truly partner, then this becomes the future of healthcare.    Add to improvements in computer vision, the rapidly advancing technologies of AI, and IoT and watch how quickly problem-solving scenario outcomes improve across all industries. Much like the last convergence of mobile phones and the internet, AIoT will usher in a new era of human history in similar fashion. Risk and Reward of AIoT, ML, and Computer Vision With greater advancement, comes greater risk and reward. As sensors and connectivity multiply across devices and industries, renewed focus should include privacy and security. Such large volumes of Data, even within the healthcare industry, can be targets for hackers as well as government entities. It may seem strange to consider this in the light of the healthcare vertical, but imagine the repercussions of denials due to medical issues or the inverse of identity theft.  The convergence of AIoT and Computer Vision technologies use complex algorithms for predictive analytics. Add Machine Learning into the mix and watch workflows streamline, simplified problem-solving unfold, and improved reliability and sustainability of data capture and how it can enhance an organization’s processes.  In the cumbersome world of healthcare and its institutions, Computer Vision, AI, IoT, and Machine Learning offer a simpatico balance between patient and provider that flips traditional healthcare upside down. Advancements within the last few years and in the coming decade are primed to bridge the gap between patient and provider. But it’s going to need Data professionals who have a passion for the industry and can guide these technologies to the next stages in their development. The Computer Vision industry is supercharged and is expected to reach $48.6 billion by 2022. Ready to see where the latest technologies can take you? If you’re interested in Computer Vision, Big Data, and Analytics, Robotics, and more, we may have a role for you.  Check out our current vacancies or get in touch with one of our expert consultants to learn more.  For our West Coast Team, call (415) 614 - 4999 or send an email to sanfraninfo@harnham.com. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Mairead Holt

Mairead Holt

27. February 2020

Quantitative Analysts, the Science Behind the Money

Quantitative Analysts, the Science Behind the Money

Did you know New York’s Wall Street, a bastion of financial institutions, investment banks, brokerage firms and more was once an actual wall built by the Dutch to repel an English invasion? Though images of skyscrapers or movie scenes from Wall Street and The Wolf of Wall Street may flash in your mind when you think of it, the world of traditional finance has changed.FinTech businesses– a merging of finance and technology – and Challenger banks are challenging the establishment – Tier 1 banking. In an industry in which traditional banking is facing a shakeup of epic proportions from Challenger banks, finance executives increasingly turn to quantitative analysts for help. Today’s analysts want to be more invested, to make a difference and take end-to-end ownership of Model Development/Credit Strategy projects.What is a Quantitative Analyst?Quantitative analysts help financial firms make decisions about risk, pricing, and invests. But, their ultimate goal is to maximize profits – whether that be by reducing risk or generating profits – using complex mathematical models to inform business decisions.Much like the word “tech” has infiltrated other industries – advertising, marketing, retail, insurance, and so on – and the need to offer both technical (hard) and business (soft) skills remains. These analysts must be able to apply scientific methods to approach data from all angles. They must also be able to translate and interpret the information into actionable insights for their firms.Get on the Fast TrackAccording to the Bureau of Labor Statistics (BLS), the financial analyst category (inclusive of quantitative analysts) is expected to  grow 16% from 2012 to 2022 making it the fastest occupation on average. Demand is high and rising which makes competition extreme for quantitative analyst roles. Below are a few ways, you can get a leg up on the competition.Check out Michael Halls-Moore, the founder of QuantStart.com, and his Self-Study Plan for Becoming a Quantitative Analyst.#Be able to think for yourself and question everything. Look for the not-so-obvious answers.Don’t get stuck in conventional models and explore new paths. Get creative.Leave your MBA at the door. Many firms are more interested in those with a scientific background – engineering, computer science, math, or physics (natural sciences).Focus programming language studies on Python, R, and C++.Attend an event at the Wall Street Technology Association (WSTA®) created to provide opportunities to learn from and connect with other finance professionals. This year they’re launching an Innovation Showcase at its annual Summer Social on June 13. This event will showcase leading-edge technology solutions and a chance to network with other colleagues in the industry. Tickets are sold out but heads up for next year. Show Me the MoneyIf you’re a master mathematician, statistician, financier, or economist, Wall Street institutions will always need Quantitative Analysts to measure risk, to analyze, and to generate profits. After all, at nearly 30% above the national average, Wall Street is where the money is.If you’re looking for a new challenge and want get your foot in the door at a FinTech start up looking to shake up the nonprime market, we have a role for you. We’re hiring for a Lead Data Scientist to take the reins to develop, deploy, and maintain a credit-based model from scratch to enable under-served and emerging markets around the world. Contact Edward Flynn, Recruitment Consultant +1 212 796 6070 edwardflynn@harnham.comCredit Risk not your thing? No worries, check out our current vacancies or contact our East Coast team to learn more.For the East Coast team please call 212-796-6070, or email newyorkinfo@harnham.com.

Jenni Kavanagh

Jenni Kavanagh

13. June 2018

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