Data Scientist Job Summary
There is often confusion surrounding job descriptions for data analyst vs. data scientist. The truth is that both of these roles are quite similar. However, data scientists can predict the future based on past observations, whereas data analysts only develop current insight from available information. Additionally, data scientists are expected to generate their own questions, while data analysis is focused on answering the existing ones.
As you’re about to find out in this data scientist job description, you’re also expected to use raw data and turn it into information that decision-makers within a company can then use to improve various parts of its business.
The amount of data collected each day is vast and can be used in a number of different ways – from determining solutions to reduce pollution from plastic packaging to predicting what people may buy in retail or ecommerce stores. To find out more information about the subject, check out the following job descriptions!
The data scientist role means the employee should solve problems or discover patterns in her day-to-day tasks. She will gather data from a number of different places, which will then need to be analyzed and interpreted using advanced methods such as artificial intelligence, algorithms, and data mining. The obtained information can be used in business decision-making processes.
As the information will be passed to other stakeholders, it needs to be both engaging and crystal clear.
Data scientists are needed across many different sectors, which has resulted in data scientist job growth in recent years. The main skills businesses tend to seek in these types of roles are strong analytical, communication, and technical skills.
This type of job is very diverse in terms of the opportunities available. In fact, there appears to be no limitation in the types of sectors in which data scientists are needed. This is something that you’ll probably realize when you next read a data scientist job description on a job board website.
Some of the most in-demand sectors for this career include academia and universities, IT, scientific research, retail, government, health, finance, and ecommerce. Other sectors that require data scientists also include telecommunications, energy, biotechnology, quality control, transportation, automotive, and internet industries.
However, this list is non-exhaustive, and lots of industries look for data science graduates, regardless of commonly perceived data scientist prerequisites. In other words, if you’ve just left university but believe you don’t yet have the necessary skills for employment, apply anyway. You may be surprised at the response you receive. Data scientist graduates are very much in demand, and companies are committed to investing in their development in the workplace. It’s also interesting to note that data scientist is the third-best career in the US.
Data Scientist Job Requirements
In terms of the subject you should choose when considering a data scientist qualification, you should pick a degree in maths, computer science, or a science-based subject. Other subjects that would make a good fit for this career include physics, statistics, engineering, and data science.
Alternatively, if you have a strong grasp for maths, you may be offered a data science role if you’ve studied economics, health, or psychology. However, you will need some knowledge in basic programming on your data scientist resume.
As part of your degree, you may develop skills in programming. The best languages to learn include R, Python, C, or Java, along with database coding and design.
If you’re recently graduated, got a degree and are looking for your first data science job, some large companies out there offer graduate schemes that typically take no longer than two years. While most data scientist training schemes have strict requirements for a related discipline, some allow graduates with any degree, as long as they show some aptitude and skills for the subject.
For career changers, a master’s degree or Ph.D. will come in useful, but make sure you’re committed to learning analysis skills.
We found that most internships tend to be with larger organizations, particularly those like retail, travel, and finance. The data scientist job description that you’ll see next will indeed clarify this. However, medium or small-sized businesses occasionally advertise data scientist roles as well.
We recommend keeping your eyes peeled during the autumn months. This is the time of year when most vacancies tend to be advertised. Although smaller companies may not actively advertise for interns, it’s sometimes worth submitting a speculative application. You may be surprised at just how many entry-level data scientist jobs become available this way.
Your chances of landing an internship within a data science role will be greater if you have some kind of work experience, even if this is something you do during your course like self-directed learning.
Another route into this career is to get involved in an online data science competition such as Topcoder or Kaggle.
Improve your data scientist job outlook by speaking to a careers adviser at your university. They can point you in the right direction and help you if you’re unsure about local internship opportunities or the skills you need to succeed in your career.
Data Scientist Skills:
- Strong presentation and communication skills in order to explain technical concepts to a non-technical audience.
- Good listening skills so that you can fully understand a business’s requirements. This is something you’re likely to develop during your data scientist course.
- An analytical mind capable of solving complex problems each and every day.
- Technical experience in using tools like SQL, Hadoop, and SAS for database analysis and interrogation.
- Self-motivated, resilient, and driven. Able to work independently without supervision and attempt new ideas if the original one didn’t work.
A data scientist job title demands a number of skills that need to be developed on the job. These include:
- Skills in time management, planning, and organization.
- Delivering projects under tight deadlines and within a potentially high-pressure environment.
- Strong attention to detail along with a good eye for errors and inconsistencies.
- Able to collaborate and share ideas as a team while attempting to find appropriate solutions.
While you are completing your graduate work placement or data scientist degree, you will have the opportunity to strengthen these necessary skills in your day to day duties.
Data Scientist Responsibilities and Duties
Tasks you may be expected to complete include:
- Creating experiments and algorithms involving data for custom reports that the whole company or specific people within it could use. This is something you may be exposed to when completing your data scientist certification.
- Identifying issues within an organization and utilize data to suggest solutions that can be used in decision making.
- Using statistical techniques or machine learning to solve problems using the best solutions.
- Testing data mining models and choose the best one to use for a particular project.
- Using clear verbal and written communication to understand requirements and create reports from data.
Other data scientist tasks and skills you’ll need to develop include:
- Reporting on how clients work with the business in a clear manner.
- Working out how good current data collection techniques and sources are, making improvements where necessary.
- Seeking chances to use datasets/code/models and insight in other departments of the business.
- Developing proof of concept and prototypes through research.
- Going beyond simply satisfying data scientist education requirements by keeping up to date with the latest techniques, methods, and technology through horizon scanning.
- Enabling other staff to see the benefits of your work and remain enthusiastic about problem-solving and algorithms.
Data Scientist Salary
As you get started in your career, expect to earn in the region of between $25,000 and $30,000 per year for an average data scientist starting salary. Once you gain a little experience, this may increase to $50,000 per year. After working a couple of years in the role, your salary could go up even further to between $75,000 and $125,000 per year.
Nevertheless, this depends on a number of factors, such as the sector you are working in, your qualifications and experience, and the location you’re based in. Depending on the organization you are working in, you may be able to benefit from flexible or remote working, a pension, private medical insurance, and a performance-based bonus.
To find out the full benefits you could expect, make sure to thoroughly read the data scientist job description before you apply.