Data is the new chief, as Data science continues to evolve as one of the most promising and in-demand career paths. Although its origin can be traced to data statistics and data analysis, since data began to evolve and become larger, those roles evolved as well. How then can we describe Data Science?
Data Science Defined
Data Science is not a certain or one specific concept, it is a combination of various disciplines that focus on analysing data to find the best solutions. It is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structured and unstructured data.
Hence, those who take on the task of gathering and analysing these large sets of structured and unstructured data are called Data Scientists. Performing this role efficiently involves combining knowledge of mathematics, computer science, and statistics. A Data Scientist analyses and processes data, then interpret the results extracted from the process to create plans for organizations.
Data scientists are analytical professionals who utilize their skills in technology and social science to detect trends and manage data. They use industry knowledge, understanding and existing assumptions – to uncover solutions to business challenges.
Data Scientists work to make sense of messy, unstructured data from sources such as smart devices, social media feeds, and emails. They make all these fit neatly into a database.
Responsibilities of a Data Scientist
Every organization will have different tasks for their Data Scientists. However, these are the responsibilities you are most likely to perform daily.
You will solve business problems through research and open-ended industry questions. This simply means asking the right questions to begin the problem-solving process.
You will acquire huge volumes of structured and unstructured data. You will query structured data from several databases using programming languages such as SQL and gather unstructured data through web-scraping, APIs, and surveys.
As a Data Scientist, you will use analytical methods, machine learning, and statistical methods to prepare data for use.
You will clean the data acquired to get rid of irrelevant information and prepare the data for pre-processing.
Your role will also include performing exploratory data analysis (EDA) to determine how to handle missing data and to look for trends and/or opportunities.
As a Data Scientist, you will discover new algorithms to solve problems and build programs to automatically repeat the solution process when a new problem arises.
You will present results and findings to management and IT departments through data visualizations and reports.
Lastly, you will recommend cost-effective changes to existing procedures and strategies. You will also give suggestions on what adjustments to make based on feedback.
Skills of a Data Scientist
- Statistical analysis: Identify patterns in data. A good understanding of statistics is essential as a data scientist. You have to be familiar with statistical tests, distributions, maximum likelihood estimators, etc. This will also be the case for machine learning. But one of the more important aspects of your statistics knowledge will be understanding when different techniques are applicable or not. Statistical analysis is important to all sectors. However, companies that are big on data where stakeholders will depend on your help to make decisions and design/evaluate experiments need these skills more.
- Machine learning: You need to understand how algorithms work and when it is appropriate to use different techniques. These include; Natural Language Processing, Classification, Clustering, Ensemble methods, Deep Learning
- Computer science: You must know how to apply the principles of artificial intelligence, database systems, human/computer interaction, numerical analysis, and software engineering as these will aid your growth in a Data Science career.
- Programming: This is probably the most important skill to have to become a Data Scientist. You must write computer programs efficiently and analyse large datasets to uncover answers to sophisticated problems. As a Data scientist, you need to be comfortable writing codes, working in a variety of languages such as Java, R, Python, and SQL, Scala, MATLAB.
- Data storytelling: You should be able to communicate insights to a non-technical audience.
- If your workplace is a business environment, you will need to have Business intuition.
To become a Data Scientist, you will need at least a Bachelor’s degree in Data Science, Mathematics, Statistics, or Computer Science. This means your secondary school subjects must be within these fields or those related to them. Your university education is more direct as a good number of schools offer coursework which cover Data Science in their Degree programs. Below are a few universities offering accredited programs.
Swansea University in the United Kingdom: Offers a BSc (Hons) in Computer Science. The tuition for international students is £ 16,650 and you can study for 3 years full-time or 4 years full-time with industry work. A Computer Science degree from this university will help you develop skills to identify Data solutions and measure their efficiency. Other transferable skills you will learn are team-working, communication, presentation, and problem-solving skills. The university also offers an MSc in Data Science, if you are interested in further study. The tuition is £ 18,000 for international students and you can choose to study for 1 year full-time or 2 years part-time.
Carleton University in Canada: Offers a B.C.S Honours in Computer Science. The tuition for international students is CAD 33,281. The degree also gives provision for concentration in different aspects of Computer Science. At Carleton University, you will learn to use computing and information technology to help solve the problems that we face in business, science, and society today, as well as those to come.
Kent State University in the United States of America: Offers a Bachelor of Science degree in Computer Science. The tuition is $21,400 for international students, however, the tuition may vary if you choose to go for a part-time mode of study. The degree will teach you how to understand, design and build complex computer software systems.
The stages of career development of a Data Scientist are:
- Data Analyst (entry-level) – Data Engineer – Business Intelligence Analyst – Data Mining Engineer – Data Architect – Data Scientist – Senior Data Scientist.
Job Outlook for Data Scientists
The US Bureau of Labor and Statistics (BLS) states that the employment growth of computer information and research scientists by 2028 is 16%. This is over three times faster than the national average. It simply shows that Data Science has rapidly become a highly desirable career path. Glassdoor has ranked data scientists as one of the 10 best jobs in America for four years – an analysis determined through the median salary, the number of active job openings, and employee satisfaction rates.
Also, Harvard Business Review called data science “the sexiest job of the 21st century,” noting that “high-ranking professionals with the training and curiosity to make discoveries in the world of big data” are in high demand. According to LinkedIn, data science was the most promising job of 2019. Indeed, Data Science will keep growing, with a lot more to offer.
Data scientists can work in basically any organization. Their typical employers include:
- Federal Government
- Computer systems design
- Research and development
- Colleges and universities
- Software companies
- Car companies
- Delivery companies
- Tech Companies
Famous Data Scientists
- DJ Patil: He is the Deputy Chief Technology Officer for Data Policy and Chief Data Scientist in the Office of Science and Technology Policy. Dr. Patil coined the term Big Data. He has worked with LinkedIn, RelateIQ, Skype, PayPal, Greylock Partners, and eBay in the past. He also worked in an important position at the Department of Defense of the United States America. DJ Patil says that Newton and Einstein have been his role models who he draws inspiration from to be what he is today.
- Yann Lecun: He is the Director of AI Research Wing on Facebook. He has 14 US patents registered under his name. He has worked on several Deep Learning experiments as well as projects and is the founder of NYU Center for Data Science. Yann is serving as a professor at New York University and has been there for the last 12 years. Machine Learning, Computational Neuroscience, Deep Learning, and Computer Vision are his areas of interest and expertise.
- Jeff Hammerbacher: He is very knowledgeable in the field of data science and was the driving force behind building the first formal Facebook Data Science team. He is the co-founder of Cloudera and works as an Assistant Professor at the Icahn School of Medicine at Mount Sinai.
- Silvia Chiappa: She is presently a senior researcher at Google DeepMind. She has a Ph.D. in AI and her research interests lie in Bayesian reasoning, time-series models, graphical models, reinforcement learning, approximate inference, and deep learning. She has co-composed a few papers on a scope of topics and additionally filled in as one of the editors for the book, Bayesian Time Series Models. Before working for DeepMind, she worked at Microsoft Research Cambridge, at the Statistical Laboratory University of Cambridge and the Max-Planck Institute for Biological Cybernetics.
Salary of a Data Scientist
A data scientist’s salary will depend on the years of experience, skillset, the education they have, and their location. According to The Burtch Works Study, employers place greater value on data scientists with specialized skills. Some of these are Natural Language Processing or Artificial Intelligence.
- The average salary for a data scientist is $123,718 per year in the United States. (indeed.com)
- The average salary for a Data Scientist is £52,752 per year in the United Kingdom. (indeed.com)
- The average Data Scientist salary in Canada is $110,000 per year or $56.41 per hour. Entry-level positions start at $38,318 per year while most experienced workers make up to $186,250 per year. (nuevoo.ca)
There are several other careers you can pursue with your knowledge of Data Science. Some of these are:
- Business Intelligence Developer: As a Business Intelligence Developer, you will have the responsibility of designing and developing strategies to assist business users. You will also help in finding the exact information they need to make sound business decisions. Business Intelligence Developers are extremely data-savvy and so they use Business Intelligence tools or develop personalized Business Intelligence analytic applications to aid the end-users’ understanding of the business systems.
- Infrastructure Architect: An Infrastructure Architect is responsible for making sure that all business systems and processes are working properly. They also ensure that these systems can support the development of new technologies/updates and system requirements.
- Enterprise Architect: An Enterprise Architect bridges the gap between business and IT in an organization. The career path emerged as a result of businesses realizing that they would need to align their business goals with their IT strategy and technological processes. This simply means that Enterprise Architects translate a company’s business strategy into concrete solutions and tailor IT processes to support that strategy.
- Cybersecurity Specialists and Database Architects are relevant careers you can also pursue in place of Data Science.
MSc Data Science (Social Analytics): This is offered at the University of Manchester. The tuition for international students is £22,500. The program’s duration is 1 year of full-time studies. An MSc in Data Science from this university gives opportunities to graduates of different disciplines to develop data science skills.
Master of Applied Data Science – Online: The program is developed by the University of Michigan. It is completely online and has a tuition of $31,688-$42,262. The duration of the program is a minimum of 12 months. It is designed for aspiring Data Scientists to learn skills that they would need to be leaders in the industry.
MSc. in Statistics: Data Science, Stanford University: There is no online option for this program, however, it remains one of the most comprehensive postgraduate studies in Data Science. The tuition is $11370-$17493, depending on the number of units you will take in total. The MSc. degree is tailored to prepare aspiring Data Scientists for the current trends in analytics and data science.
Professional Certifications in Data Science
CAP was created by the Institute for Operations Research and the Management Sciences (INFORMS) and is targeted towards data scientists. During the certification exam, candidates must demonstrate their expertise in the end-to-end analytics process. This includes the framing of business and analytics problems, data and methodology, model building, deployment, and life cycle management. The base charge for a CAP certification is $695.
The CCA exam tests your foundational knowledge as a developer, data analyst, and administrator of Cloudera’s enterprise software. Passing a CCA exam and earning your certification will convince your employers that you have adequate knowledge of the basic skills required to be a data scientist. It is also a great way to prove your skills if you are just breaking into the world of data science. It is equally useful if you don’t have a strong resume or past work experience. The certification includes a $295 charge per exam and attempt.
For further guidance on schools offering courses that are tailored towards a Data Science career, you can leave a comment or send me an email right away.