With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.
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Your résumé got you noticed and you excelled in interview. The interview discussions should have covered all the questions you may have concerning the role. Now you’ve achieved your goal and been offered the job!
Initial elation is all too often followed by a few reservations as reality bites; Is it really the job for you? Are you up for the challenge? And longer term is it going to offer you the right career path you wish to take?
It is absolutely normal to have some doubt, after all this new job, the new responsibilities, environment, commute and colleagues will make up your working life for the foreseeable future. At this stage you really should have all the information you need to be able to immediately accept the offer. But if you do need to have a final review before accepting, our advice is to do it quickly. Consider the fundamental aspects of the role and make sure they will really suit you in the medium to long term. Then take the following into account and check they meet your needs before you sign that new contract.
What kind of culture does your potential new employer have? Do they value a work hard/play hard ethos? This sounds like a great environment but can be demanding if you have family commitments outside work. On the flip side this could be exactly what you are looking for! Are they people-oriented or result-oriented? What is their vision, values and mission statement?
Whatever the company culture is, it really should be one that suits your personality, values, goals and beliefs. Imagine having to do work which you disagree with day-in and day-out. If you are at a stage in your career/life where you want work to be your main focus while you develop your experience and skills – will the work environment allow for this? Does the company culture involve regular socializing as well as working together – will this have any impact on your current social life/outside work commitments? These may not be major considerations but just take a moment to be make sure they are not a priority to you.
Do you feel confident that the personalities you will be working with are ones you will get on with? You will be spending almost more time with these people than anyone else so it is key that, while you may be different in character, there is a connection in terms of attitude to work and the best interests of the company you work for. A supportive network of colleagues and an understanding boss would definitely make your work a more harmonious place to be.
Of course, it’s hard to tell a huge amount about someone’s personality and character from an interview alone, so this is where you may have to rely on gut instinct. Just as their first impression of you matters during the interview, the impression you gleaned of your potential new boss and/or colleagues matters just as much. They should have taken the time to prepare sufficiently enough to convince you to join the company and their team, which is a good indicator of aspects of their working style with their staff/team.
When it comes to colleagues, it would be good to find out what the demographic is across the rest of the team. While we can’t choose our work colleagues it would be good to have something in common with some of the team, this may seem minor but it will guarantee at least some common topics of interest during your daily conversations with them. Having said that some teams have a great dynamic because they are all completely different – a team with diverse backgrounds offers a really stimulating work environment for some.
During the interview, you will have been briefed on the scope of the role and what you will be expected to have responsibility for. However, we all know that we’re not simply employed to fulfil the basic job function; we will always get additional tasks and projects from time to time. What you need to find out is, how often these ad-hoc items will crop up - how much does the company expect employees to perform ‘beyond the call of duty’? If everyone’s expected to do more than is required, then what do you have to do to get noticed? On the other hand, if you’re not counted on to assume additional work, you will definitely be able to stand out if you do make that extra effort.
Does the career progression match your needs?
Progression or stability, this is personal to you. What matters most is that you make an informed choice based on what the organization has to offer to you. How frequent do employees of a similar position as yours get promoted, and how often do they leave the job? You might even consider the bigger picture and consider if the industry is stable or in a period of growth, or static.
If your priority lies in climbing the career ladder, you need to find out what it takes to get promoted. Generally speaking, the more competitive the culture, the more you need to do to impress and progress! This will have an impact on your work-life balance and even your physical and mental health. You’ve got to see if such pressured and potentially stressful working conditions are really right for you.
Depending on your individual circumstances, you may prefer stability over prospects. For that, it might be helpful to find out what the staff turnover rate is for your prospective team/department. Can your prospective employer offer progression with stability? This really would be the ideal scenario, whatever type of role you have been offered.
Your consideration should be that you are being offered a package which matches market rates for the skills and experience you offer. Talk to your recruitment consultant – they will have in-depth knowledge on your sector and will be able to advise accordingly. If you applied direct to the company, you should have already compared salaries for the role in questions. Remember also to take into consideration the company benefits too, such as insurance, training programmes, annual holiday entitlements, discounts on products/services etc.
In summary, a number of the factors mentioned should be considered long before a job is offered but it is worth just reviewing them all before you do commit. And, if you have considered all these fundamentals and everything is a positive then what are you waiting for – get that contract signed!
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 News & Blogs portal or check out our recent posts below.
What do you get when you combine Amelia Earhart with Ada Lovelace? A Data Visualization Engineer ready to work with an aviation industry partner. Reaching new heights and shattering the glass ceiling is the modus operandi for many women, and what better role models than the ladies listed. Creative, free-spirited, pioneering, and well before their time in thoughts and action. Ada Lovelace, now attributed as the first computer programmer saw beyond the automatons of her day. She saw beyond the Berullean language in front of her she was translating. A poet father and a passion for numbers collided into her thoughts and as we marvel at AI making art, writing stories and music, and winning strategy games, we have one lady to thank. Ada. She might also be called the first Data Visualization Engineer. Don’t you think? Insightful Business Decisions are Key in Collaboration Data professionals are no longer siloed from other departments in business allowing for collaboration between teams. In partnership between both technical and non-technical employees, businesses can be sure they’re teams have a single vision to help realize business objectives and goals. The collaboration between Ada Lovelace and Charles Babbage may not have been business-related, but the ideas are the same. He passed her the document and asked her to translate, she made notes, and those notes have made history. Together they created a vision for The Analytical Machine – it exists only on paper, but it’s design, layout, and potential implementation are realized in ways unimaginable to most 100 years ago.Ada’s mathematical prowess was such that she wrote her notes in easily explainable language.She worked closely with Charles Babbage and wrote in earnest to work with Michael Farraday – she reached out to others in her field, some accepted, others didn’t. How Data Helps Inform the Future Whether you use predictive modeling, machine learning, natural language processing, or some combination of each, the data you collect helps to inform the future. We may often lament the old adage that those who don’t know their history are doomed to repeat it, but history has a shining light as well. Collaboration across the ages. Consider this. Alan Turing, the man who worked in Bletchley Park with the Enigma machine, used the notes he found to help him solve the problem. Those notes belonged to Ada Lovelace. The information she set to paper informed every stage of computer programming leading to what we know today as Artificial Intelligence. Machines that could learn and ‘think,’ not just the automatons of her age which had been ‘programmed to perform.’ The Enchantress of Numbers Known as the Enchantress of Numbers, the pioneering Ada Lovelace shares the spotlight with other pioneering women in the sciences. Think Madame Curie, Joan Clarke, even Hedy Lamarr, and of course Amelia Earhart. They weren’t of the same eras, but each of their contributions have added to what we know as the Science, Technology, Engineering, and Mathematics (STEM). We have a name for it now, but it’s always been around. And the collaborative efforts of women everywhere are growing and increasing diversity and inclusion in many businesses across the world. And at the heart of it all, in the beginning, a surprising and time-defying collaboration began. It set in motion a spark of business intelligence and insight as men and women mentored and partnered for the sake of their vision of the future. Who will be remembered one hundred years from now? If you’re interested in Big Data, Web Analytics, Marketing & Insight, Life Science Analytics, and more, check out our current vacancies or contact one of our recruitment consultants to learn more. For our West Coast Team, contact us at (415) 614 - 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
22. October 2020
2020. It sounds like the name of a futuristic science-fiction movie or TV show, doesn’t it? Maybe it is. And like our favorite sci-fi flicks there are cutting edge changes happening in real time. We’re the characters in this story and the Computer Vision and Artificial Intelligence partnerships in healthcare are moving fast to help us take care of ourselves. When computers can see what we can’t. When AI can help us make more informed decisions. When the two are combined to help doctors and providers work more efficiently to save lives, that’s when the cutting-edge shines. From the collaboration of Johns Hopkins, the CDC, and the WHO mapping out the data to contact traces to medical professionals on the front lines, we’ve been focused on one thing. Saving lives. But, what about the other medical issues that affect us? Heart disease. Cancer. Neurological illnesses. What if the latest advances in healthcare could help here, too? Five Ways Computer Vision Helps Healthcare Providers Identifies leading causes of medical illnesses in a time-sensitive manner by creating algorithms for image processing, classification, segmentation, and object detection.Develops deep learning models to create neural networks.Collaboration of teams of scientists working together for the advancement of projects and present findings to business leaders, stakeholders, and clients.Allows providers to spend more time with their patients.Optimization of medical diagnoses using deep learning so doctors can spend more time with patients to help see and solve the problem faster. Computer Vision Engineer Meets AI Professional Artificial Intelligence (AI) offers real world answers in healthcare the world needs today. Computer Vision Engineers build the means to which AI helps providers, patients, and leaders make informed decisions. Core requirements for both roles include, but aren’t limited to: Experience in machine learning and deep learning.How to build computer vision algorithms and probability models.Problem-solving skills, creativity, ingenuity, and innovation.Languages like Python, R, Hadoop, Java, and Spark.Be able to see the big picture while at the same time finding the devil in the details. Always striving to improve, to make better, to advance the technology within the industry. The Challenges and the Potential of Technology in Healthcare At the moment, Computer Vision, AI, and other healthcare technology models are localized to individual placements. The next step is to have these technologies ‘speak’ to each other across hospitals, provider’s offices, telehealth applications, and electronic health records management for a more cohesive benefit of care. As this year rounds to a close, we know the vulnerabilities of our healthcare system, and can find solace in the though that technology is bringing it forward at lightning speed. Automation and telehealth appointments have made it a breeze to talk to our doctors and get results faster. We can pay our bills with the click of a button and even carve out a payment plan, if need be. All without leaving our homes. The data now available to us and our providers offers a foundation, a benchmark of information, so our doctors can make more informed decisions. This data goes beyond the individual, it helps set a precedent for not only individuals, but also entire populations, to help us identify future health issues, epidemics, and pandemics. Stored data is private and stays within its construct of hospital or doctor’s office, but from it we can create models to plan for the future. Want to make your make your mark in the healthcare and tech industry? We may have just the 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, contact us at (415) 614 - 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
15. October 2020
Philadelphia. It’s known for it’s Philly Cheesesteak, the Liberty Bell, and where the Constitution was signed. Always on the cutting edge, Philadelphia is a land of firsts. You may or not know this, but one of its firsts was to have the first general use computer in 1946. Is it any wonder then that a company there is building robots to navigate GPS denied environments and was begun by leaders in the Computer Vision space? Beyond the Roomba If you consider the Roomba, the autonomous vacuum that sweeps up pet hair, dirt, and other unwanted product, how does it know where to go? How does it know to go under a table or chair or around a wall to the next room? How does it know to avoid the dog, cat, or you? On nearly the smallest scale, this little round machine is a personal version of simultaneous location and mapping (SLAM). However, the computational geometry method of this mapping and localization technique extends in a wide variety of arcs. Here are a few to get you thinking: GPS Navigation SystemsSelf-driving carsUnmanned Aerial Vehicles (UAV)Autonomous Underwater Vehicles (AUV)DronesRobotsVirtual Reality (VR)Augmented Reality (AR)Monocular Camera...and more There’s even a version which is used in the Life Sciences called RatSLAM. But we’ll visit that in another article. The uses and benefits of this simultaneous location and mapping technique are exponential even with some of the challenges posed by Audio-Visual and Acoustic SLAM. What is SLAM? Essentially, it is the 21st century version of cartography or mapping. Except in this case, not only can it map the environment, but it can also locate your place in it. When you want to know where the nearest restaurant is, you simply type in ‘restaurant near me.’ And soon, a list appears on your phone with a list radiating from nearest location outward. Imagine you’re lost on a hike, you manage to find signal, and soon your GPS is offering directions on which way to move toward civilization. This is Simultaneous Localization and Mapping. It locates you, your vehicle, a robot, drone, unmanned aerial vehicle or self-driving car and puts people and things in the direction it thinks they want to go or should go to get to safety. While mapping is at the epicenter of SLAM Computer Vision Engineering, there are other elements within the field as well. But let’s begin with mapping. Topological maps offer a more precise representation of your environment and can therefore help ensure consistency on a global scale. Just as humans do when giving directions, sensor models offer landmark-based approaches to make it easier to determine your location within the map’s structure and raw-data approaches which makes no assumptions. Landmarks such as wifi or radio beacons are some of the easiest to locate, but may not always be correct which is where the raw-data approach comes in to offer its two cents as a model of location function. Four Challenges of SLAM GPS sensors may not function properly in chaotic environments such as military conflict. }Non-static environments such as pedestrians or high traffic areas with multiple vehicles make locations difficult to pinpoint.In Acoustic SLAM, challenges include inactivity and environmental noise as well as echo. Sound localization requires a robot or machine to be equipped with a microphone in order to go in the requested direction. Five Additional Forms of SLAM Tactile (sensing by touch)RadarAcousticAudio-Visual (a function of Human-Robot interaction)Wifi (sensing strength of nearby access points) Ready to Explore a Robotics and Computer Vision Career? Whether you’re interested in a slam dunk career as a SLAM Engineer or looking for your first or next role in Big Data, Web Analytics, Advanced Analytics & Insight, Life Science Analytics, or Data Science, take a look at our current vacancies or get in touch one of our expert consultants to learn more. For our West Coast Team, contact us at (415) 614 - 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
08. October 2020
In the early days of 2020, Johns Hopkins, the CDC, the WHO, and a host of other public organizations banded together in collaboration. They were on a mission to ensure the world had real-time information to a virus that would forever chance the course of this year and the years to come. Which is great for those families with a computer in every home or every person with smartphone access. But what about the rest of the world? How do you ensure those people without access to basic needs lives can be improved? A health non-profit using AI and Machine Learning is aiming to do just this. But the Data is vast and the sheer numbers of people need to be corralled by someone into something the computers can read and make decisions on. Who would have thought Public Research and Data Science would come together in such a manner and in such an important time? Three Benefits of Data Science and Machine Learning in Healthcare According to a seminar given in September 2019, two research scientists explained to the CDC the promises and challenges using Big Data for public health initiatives. After explaining a few definitions and making correlations, the focus was soon on the benefits. The focus of Machine Learning is to learn data patterns.From the initial focus, patterns can then be validated to ensure they make sense.These patterns and validation of patterns can find links between seemingly uncorrelated factors such as the relationship between one’s environment and their genetics. To the scientists working with these scenarios, the decisions seem simple. Yet, when it comes to explaining them to laymen like policymakers, there can be a shift in understanding. This shift can lead to arbitrary and different findings which can affect medical decision making. Why? Could it be using Random Forests in linking the data could be confusing? Data Classification is Not as Cut-and-Dried as a Work Flow or Org Chart If someone shows us a work flow or organizational chart, we understand immediately each task to be done in which order or who reports to whom. But in trying to link uncorrelated bits of information using decision trees, it can seem more like abstract art, more subjective than direct. Yet, it is those correlations which answer the bigger questions brought to bear by Research Scientists, Public Health Researchers, the Data Scientists, and AI working together to see the bigger picture. Decision trees, ultimately, are the great classifier. But there are a few things which need to be in place first. Yet, in the random forest model it’s not just one decision tree, it’s many. This is definitely a case where, if you done right, you will see the forest for the trees and at the same time be able to determine patterns in those trees. A bit counter-intuitive, but this is what stretches our minds to see correlations and patterns we might not see otherwise, don’t you think? So, what do you need to help make predictions? Two Important Needs to Help Make Predictions Predictive power. The features you employ should make some sense. For example, without a basic knowledge of cooking, you can’t just throw random items from your refrigerator into a pot and expect it taste good. Unless of course, you’re making soup and all you have to do is add water.The trees and their predictions should be uncorrelated. If you’ve ever seen M. Night Shymalan’s Lady in the Water, there’s a little boy who can ‘read’ cereal boxes and tell a coherent story. A predictive coherent story. This is the layman’s version of random forests, their predictive nature, and ultimately, the scientists who can ‘read’ and explain the patterns. If you're looking for your first or next role in Big Data, Web Analytics, Marketing & Insight, Life Science Analytics, and more, check out our current vacancies or contact one of our recruitment consultants to learn more. For our West Coast Team, contact us at (415) 614 - 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
01. October 2020