What is a Data Scientist?
Data Scientist jobs are to gather, process, and analyze large sets of structured, unstructured data. Data Scientist jobs are to combine statistics, mathematics, and computer science. Companies and other organizations use their analysis skills, process and model data before interpreting the results and developing action plans.
Data scientists use their knowledge of both technology and computer science to analyze data and find trends. They can deliver solutions for business challenges based on their knowledge of a wide range of industries and their contextual awareness. In a standard Data Scientist job, scientists make use of messy, unstructured data gathered from platforms such as mobile devices, social media sites, and messages that do not map seamlessly into databases.
What does a Data Scientist do?
Data scientists are mandatory assets and can be found in almost every organization. Traditionally, these professionals are data-driven, well-rounded professionals with high-level technical skills who can synthesize and organize large amounts of information to answer questions and drive organizational strategy. Effective communication and leadership skills are also required to deliver concrete results to various stakeholders throughout an organization.
To explain highly technical results to their non-technical counterparts, data scientists must be curious, result-oriented, and have superior knowledge of their industry. With a solid background in statistics and linear algebra, these individuals possess strong programming skills that focus on data mining, data warehousing, and algorithm analysis to build and analyze algorithms.
Data Scientist’s job duties include:
As far as the Data Scientist job is concerned, there is no clear description. However, here are some typical responsibilities you may have:
- A large amount of unruly data can be gathered and transformed into more usable formats.
- Using data-driven techniques to find solutions to business problems.
- Possesses knowledge of SAS, R, and Python programming languages.
- An understanding of statistical tests and distributions as well as statistical tests.
- Achieve excellence in the application of analytical techniques, such as machine learning, deep learning, and text analysis.
- Communication and collaboration between IT and business.
- Data analysis is the process of finding order and trends in data and identifying trends that can improve an organization’s profitability.
Job brief for Data Scientist
A Data Scientist job is filled with an individual with a strong understanding of data mining/data analysis methods, data tools, building and implementing models, utilizing/creating algorithmic techniques, and running simulations. Recruiters are looking for those with the below necessary skills.
- Ability to solve problems analytically and creatively
- Interrogation and analysis of large databases in Hadoop, SQL, and SAS
- Communicate and present your work clearly to people who do not understand the mechanics of data analysis
- Understanding the requirements of the business requires effective listening skills
- If your first attempt fails, be resilient and try once again – you’ll be working with little supervision, so you’ll need to be self-motivated
- Organizing, planning, and time management skills
- The ability to meet tight deadlines and deliver under pressure
- Detail-oriented
- To share ideas and find solutions, you need team working skills and a collaborative approach.
Responsibilities of Data Scientist
- Using undirected research to make business decisions and formulate open-ended industry questions
- Extract huge volumes of unstructured and structured data. Use languages like SQL to query structured data stored in relational databases. By scraping the web, utilizing APIs, and conducting surveys, they gather unstructured data.
- Prepare data for predictive and prescriptive modelling by employing sophisticated analytical methods, machine learning, and statistical methods.
- Clean and prepare the data to be preprocessed and modelled by removing irrelevant information
- To identify gaps in data as well as trends and opportunities, perform exploratory data analysis (EDA)
- The development of new algorithms for solving problems and creating repetitive task-automation software
- Visualize and report data effectively for management and IT departments to receive predictions and findings
- Cost-effectively change existing strategies and procedures.
Requirements for Data Scientist
- Fluency with several software programs, including Python, SPSS, SAS, MATLAB R, Java, Hadoop Platform, C/C++, SQL/NoSQL Databases.
- Understanding of business logic and objectives: Data scientists need to be able to think like a business owner or manager and come up with reasonable solutions for complex problems.
- Data scientists can communicate their technical and analytical information clearly and fluently to a non-technical audience. For proper data analysis, they should also understand the needs of their non-technical departments. The data scientist must present reliable, verifiable information to the business so it can make informed decisions.
Average Salary for Data Scientist jobs
The average salary for Data Scientists in Singapore can vary based on experience, specific employer, and industry.
General Salary Overview
- Entry-Level (0-2 years of experience): Approximately S$50,000 - S$70,000 per annum.
- Mid-Level (3-5 years of experience): Approximately S$70,000 - S$100,000 per annum.
- Senior-Level (5+ years of experience): Approximately S$100,000 - S$150,000 per annum.
Salary by Industry
| Industry | Average Annual Salary |
|---|---|
| Information Technology | S$90,000 |
| Financial Services | S$85,000 |
| E-commerce | S$80,000 |
| Telecommunications | S$75,000 |
Salary by Top Employers
| Company | Average Annual Salary |
|---|---|
| DBS Bank | S$120,000 |
| Singtel | S$110,000 |
| OCBC Bank | S$105,000 |
| Accenture | S$100,000 |
This overview indicates that Data Scientists in Singapore can expect varying salaries based on their experience and the type of employer. The demand for skilled data scientists is significant as organizations increasingly focus on data analytics and business intelligence.
Key Skills
- Python, Scala, SQL, Java, MATLAB
- Deep Learning, Natural Language Processing, Clustering, Classification, Ensemble methods
- Tableau, D3.js, Python, SAS, R libraries
- MongoDB, Microsoft Azure, Cloudera, Oracle
Why pursue a career as a Data Scientist?
Since data has become more accessible in recent years, data scientists are no longer only needed by large tech firms. There is a chronic shortage of qualified candidates available across industries big and small when it comes to filling open positions in the field of data science. No sign of filling up in terms of a Data Scientist job is visible shortly. Several data-science-related skills are included in the list of most sought-after jobs by companies in 2021, along with this career path.
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How to Become a Data Scientist?
Get a data science undergraduate degree – To get started as an entry-level data scientist, you will need a degree in data science, computer science, or a related field, although most jobs require a master’s degree. In addition to adding structure to your résumé, degrees also allow you to gain internships, network and show your academic qualifications. However, if you received your bachelor’s degree in a different field, you may need to take some online short courses or attend a Bootcamp to develop your skills for the Data Scientist job.
Think about specializing – Scientists who specialize in the field may develop their skills in areas such as artificial intelligence, machine learning, research, and database management. If you seek to earn more money and make a positive impact on the world, specialization is a great option.
Start your career in a Data Scientist job position – Your first data science role should be ready for you once you’ve gained the right skills. If you are looking to find a job, you may want to create an online portfolio to demonstrate your achievements. A company with room for growth might also be a good choice since your first data science job might not have a title like data scientist, but more of an analytical role. As you learn how to work with a team and how to use best practices, you’ll be prepared for more senior roles.
FAQ on Data Scientist
Q1. What is a Data Scientist?
A1. A Data Scientist analyzes large sets of structured and unstructured data, using techniques from statistics, mathematics, and computer science to solve business problems and identify trends.
Q2. What does a Data Scientist do?
A2. They gather, process, and analyze data, build models, and apply machine learning to solve business challenges. They also communicate findings to non-technical stakeholders.
Q3. What are the typical responsibilities of a Data Scientist?
A3. Responsibilities include extracting and analyzing data, developing machine learning models, cleaning data, creating algorithms, and reporting insights to management.
Q4. What are the requirements to become a Data Scientist?
A4. Key requirements include proficiency in programming languages (Python, R, SQL), strong analytical skills, knowledge of machine learning, and a degree in data science or related fields.
Q5. What are the key skills needed for a Data Scientist?
A5. Key skills include programming (Python, R, SQL), machine learning, data visualization, statistical analysis, and database management.
Q6. What industries hire Data Scientists?
A6. Data Scientists are in demand in tech, healthcare, finance, retail, government, consulting, and manufacturing.
