Forensic science can be defined as the application of scientific methods and principles to solve crimes and other types of legal issues. In most criminal cases, a forensic scientist is typically involved in looking for and examining many kinds of physical evidence that can help establishing a link between a suspect of committing a crime and the scene of the crime or victim. Forensics is now a more popular subject since several TV shows became successful, such as Crime Scene Investigation (CSI).
However, very few people realize that being a CSI or forensic professional can be a very good career alternative. One can put forward many reasons that make forensic science one of the best career prospects nowadays. The reasons range from labor market, salaries, benefits to training availability and beyond.
The availability of jobs for someone seeking to be a forensic professional used to be very small for a long time until about five years ago, when many technological and scientific advances started to develop and provided new kinds of tools that substantially improved the efficiency of the police and security forces in solving crimes and other problems. As a consequence, most law enforcement agencies and other institutions greatly expanded their resources and facilities in order to increase their ability to employing techniques and methodologies of forensic science.
Even though police departments alone employ (and keep hiring) thousands of people coming from diverse areas of forensic work and with many different educational backgrounds, police is not the only alternative for those looking for a job related to forensic science or criminal justice. Methods and concepts of forensic science are increasingly being used by many other institutions for diverse purposes so the job market for forensics is greater than ever. Companies that develop, improve and produce tools, reagents, kits and devices to be used in forensic investigation are also a good part of the available job market. The size of the job market and the opportunities associated greatly increase if one considers working abroad. Besides the United States, countries like Britain and Australia are also part of this trend.
Being a discipline that relies strongly on technology, working in forensic science requires the acquisition of certain skills. This means somebody wanting to work in forensics needs at least some sort of higher education. The type of degree and the length of the program vary largely and depend on the kind of work one is interested in doing. Some positions require higher degrees such as Ph.D. or Masters, but many more posts can be taken after a short course of one or two years earned at smaller private academies.
But these requirements are not a big obstacle to be sorted out if one considers the many benefits of working for a forensic department. Positions at police agencies and other law enforcement institutions are often accompanied by substantial benefits and competitive salaries and, best of all, good prospects of stability and professional growth along with an aura of social approval typically associated with law and order public service. These and many other reasons make forensic science on of the best career alternatives available today.
Being regarded as the hottest job by Harvard Business Review does not assure an individual that it is a promising career. This question needs to be answered in a proper way. Analysis of this topic will be done in this article so that it enables the reader/interested person in deciding whether to take it up as a career or not.
A number of courses are available offline and online that allow an individual to learn the basics of data science and get a certification. These organizations can be established ones like Google, Harvard and Adobe or can be other private organizations that have earned a name by getting their students placed.
The courses can be specialized ones or general to give an idea of data science and getting the students ready to explore the world of data science. This course is considered to be an ever expanding one and needs a student to give ample amount of time to reflect on and be creative to bring out new things in the data science field. This is something that would never get out of fashion as the creativity skill can never be a forte of a machine.
For the youth, this question holds importance. The learning part becomes the foundation for the package that would be provided to a learner. It can be done by a fresher or existing job holders. The fresher can further get experience in the field. The job candidate can get promotions on the basis of the certification as this is in demand. This field is considered to be the most rewarding in the current scenario as well as in the days to come. People with good command over machine learning and statistical tools with mathematical touch can pursue their career. Yes, it demands a lot, but the hikes are also lucrative as the skill is not available in the market. As the competition increases in the global market and more and more companies fight for the demand absorption to maximize profits, the analysts are the professionals that are looked upon by these business houses. They promise high packages in lieu of the success of the projects. Many websites have rated it as the most rewarding job of the year.
Giving a clear number in terms of the package is not made in the article. This is because the compensation provided by different organizations varies according to the type of work. But as the world ascends even more towards the information age, data, science becomes an indispensable job that would only gain importance. The accuracy of a professional and good command over the tools would ensure the growth in this sector.
To conclude, no doubt, this is going to be a career that one can follow. Being a part of the smart age, this is a job made for a person who is smart with number crunching and analysis skills. If you are someone who enjoys doing it, then go for it.
Data science employs concepts and methods of data analysis, machine learning and statistics to derive an understanding and analysis of the data related phenomenon. Disciplines of Mathematics, Statistics, Computer science, and Information technology contributes to their theories and techniques in the establishment of the field of Data Science. The establishment of Data science as an independent term is a recent phenomenon. Earlier, it was used as an alternative for the term Computer Science. Interaction of data with certain processes and representation of data through various program forms the study area of computer science. The manipulation, storage, and communication of digital information require proficient use of algorithms. Computer Science facilitates the usage of these algorithms. A Computer Scientist learns to design software systems and gains in-depth knowledge of the theory of computation.
Knowledge of data helps you ask appropriate questions and derive insights from big data, it teaches you how to manipulate data sets and allows you to gain the skill of visualization of your own findings in a convincing manner. A well-designed course trains you about how to handle data science tools. The tools which build the foundation are Mathematical tools and computational tools. The in-depth understanding of these tools and proficiency in handling these tools helps one in suggesting data-driven solutions in the business.
Mathematical and applied are two aspects and to learn data science, one has to gain an understanding of both of these aspects. Probability, statistics, and machine learning come under the scope of Mathematical aspect while applied aspects help you gain knowledge of data science, languages which includes Python, MATLAB, JAVA, SQL. It also helps gives you an understanding of the usage of the specific toolkit. The applied aspects let you into the real data world. Training in a data science course gives you expertise in the collection of big data as well as its analysis and cleansing. This training assists you in executing analysis of big data on a large scale. It also trains you on how to communicate your findings in a compelling manner.
The term which shares a very close association with data science is Machine learning. Machine learning deals with algorithms to draw patterns out of data and to make predictions. For this purpose of making predictions and drawing out patterns, machine learning employed methods of data modeling. While making predictions, machine learning trains predictive models by making use of tagged data. The awareness of ground truth gives rise to observations which qualify themselves as tagged data. This task of making prediction includes training of models to enable them on how to prefigure the unknown data from tagged data. The training of models can be done by employing various methods. While some of these methods are simple, like regression, the others are complex, like neural nets. While discovering patterns out of data, machine learning tries to look for some patterns or search for some data associations in a situation where tagged data is absent. While there are more categories to machine learning, these two comprises of the core categories.