Associate Data Analyst

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Data analysts are experts in deciphering complex raw data and transforming it into actionable insights. They excel in organising, analysing, and interpreting large data sets by leveraging a variety of analytical tools and methodologies.

In today's data-driven world, these skills are in high demand as they play a crucial role in uncovering valuable insights and driving data-informed strategies to help organisations maintain a competitive edge. Combined with Singapore's dedication to fostering a robust data analytics ecosystem, the demand for skilled data analysts will continue to grow.

With an average annual salary of approximately S$60,000 (SalaryExplorer), data analysts are highly valued in Singapore's job market. As digitalisation accelerates, their significance in guiding businesses toward data-informed decision-making has never been more essential.

What do Data Analysts do?


As a data analyst, your job scope revolves around collecting, cleaning, organising, and interpreting large sets of data using various analytical and statistical tools. You work with data from various sources, such as databases, spreadsheets, and software applications, to identify patterns, trends, and insights that can help your organisation optimise its operations, increase efficiency, and reduce costs.

In addition, you will be often tasked with creating predictive models and forecasting future trends based on historical data. Your insights and recommendations can be used by your organisation to make data-driven decisions, such as identifying new business opportunities, improving customer experience, and optimising marketing campaigns.

Overall, as a data analyst, it is critical to help your organisation stay competitive and adapt to the rapidly changing business landscape. Your expertise in handling and interpreting data is highly valued and sought after in today's global job market.

Responsibilities


  1. Collect, clean, and organise large sets of data from various sources such as databases, spreadsheets, and software applications
  2. Use analytical and statistical tools to identify patterns, trends, and insights in data
  3. Develop data analysis methodologies and models to extract insights from data
  4. Create reports and visualisations to communicate findings to stakeholders
  5. Collaborate with other teams and departments to ensure data integrity, accuracy, and consistency
  6. Analyse data to identify opportunities to optimise operations, increase efficiency, and reduce costs
  7. Develop and implement predictive models to forecast future trends based on historical data.
  8. Stay up to date with new technologies and tools to continuously improve data analysis processes
  9. Provide recommendations and insights to decision-makers based on data-driven findings
  10. Maintain data security and confidentiality by adhering to data privacy regulations and company policies

Average salary

average salary

$3,337 per month for Junior Data Analyst

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$6,999 per month for Senior Data Analyst

Skills Required for this Role

Technical Skills & Competencies

Generic Skills & Competencies

  • Budget
  • Business innovation
  • Business needs analysis
  • Business performance management
  • Data analytics
  • Data engineering
  • Data ethics
  • Data visualisation
  • Database administration
  • Design thinking practice
  • Networking
  • Project management
  • Stakeholder management
  • Interpersonal skills
  • Resource management
  • Sense making
  • Transdisciplinary thinking
  • Virtual collaboration

Career Support

Career Agility Hub

Career Agility Hub

Enjoy access to NTUC LHUB’s Career Agility Hub (CAH) throughout the SCTP programme. This recruitment platform offers over 100,000 jobs across sectors and levels, along with updates on job fairs and industry events.

Continued Career Support

Continued Career Support

Tap on career coaching and placement support services provided by NTUC LHUB and its network of partners. Additionally, enjoy continued access to CAH and receive announcements of curated jobs and job fairs via email.

 

Pre-requisites

  • Singapore Citizens, Singapore permanent residents, and holders of Long-term visit pass plus (“LTVP+ Holders”) who are aged 21 years old and above
  • Committed to complete the programme
Functional / Technical Competencies

  • Minimum NITEC
  • Be able to speak, listen, read, and write English at a proficiency level equivalent to the Employability Skills Workforce Skills Qualification (ES WSQ) Workplace Literacy (WPL) Level 6
  • Be able to manipulate numbers at a proficiency level equivalent to ES WSQ Workplace Numeracy (WPN) Level 6
  • Well versed in all Microsoft Office applications, especially Excel, Word, PowerPoint, and Outlook
  • Committed to complete the programme
Generic Competencies

  • Strong communication skills and problem-solving skills
  • Ability to multitask
  • Ability to work in a team environment
  • Maintains high integrity and displays reliability
Selection Criteria

  • Interested participants should apply for the programme
  • Shortlisted candidates will be called for a 15-minute face-face or virtual interview

Training Methodology

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Instructor-led Virtual Training

Lecture and activity-based training with certified Trainers

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Online Learning

Self-paced learning via e-learning platforms

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Portfolio Building

Create a winning portfolio filled with hands-on projects that will help you shine in interviews.

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Mentorship

Your mentor is your partner-in-Project Management. They are instructors and industry practitioners dedicated to your future success.

Duration & learners schedule

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Total duration: 276 Hours / 35 Days

This programme is offered in both full-time and part-time mode. The duration of the full-time programme will be 3 months and the part-time programme will be 9 months.

List of Courses to Attend

As part of this programme, learners must attend the following courses:
  • Data Analytics and Machine Learning Concepts for Professionals
  • Modern Approach to Analysing Business Data using Microsoft Excel
  • Excel Unleashed: DAX, Solvers and Decision Analysis
  • Querying Data with Microsoft Transact-SQL

Certifications

Participants will be awarded with NTUC LHUB Certificate of Completion .

 

Course Fee and Government Subsidies
SCTP – Associate Data Analyst

 

Before GST

After GST*

Full Course Fee

$19,000.00

 $20,710.00

Singapore Citizens and Singapore Permanent Residents aged 21 years and above 1 (70% funding)

 $5,700.00

 $6,213.00

Singapore Citizens aged 40 years and above 2 (after 90% funding)

 $1,900.00

 $2,413.00

Singapore Citizens eligible for Additional Funding Support 3 (after 95% funding)

 $950.00

 $1,463.00

*GST payable for all funding-eligible applicants: $513.00 (As per SSG’s policy, the GST payable is calculated based on prevailing rates of 9% after the baseline funding subsidy of 70 %)

  1. Base Subsidy - Eligible Singapore Citizens and PRs aged 21 years and above can enjoy subsidies up to 70% of the course fee. 
  2. Mid-career Enhanced Subsidy (MCES) – Eligible Singapore Citizens aged 40 and above can enjoy subsidies up to 90% of the course fee.  
  3. Additional Funding Support (AFS)- Eligible Singapore Citizens that meet at least one of the following eligibility criteria can enjoy subsidies up to 95% of the course fee:
    1. Long-term unemployed individuals (unemployed for six months or more); or
    2. Individuals in need of financial assistance – ComCare Short-to-Medium Term Assistance (SMTA) recipients or workfare Income Supplement (WIS) recipients; or
    3. Persons with Disabilities
Funding Eligibility Criteria
  1. Trainee must be a Singapore Citizen, Singapore Permanent Resident, or LTVP+ Holder aged 21 years old and above
  2. From 1 October 2023, attendance-taking for SkillsFuture Singapore's (SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.
  3. Trainee must achieve at least 75% attendance for each module
  4. Trainee must pass all prescribed tests / assessments and attain 100% competency.
  5. NTUC LearningHub reserves the right to claw back the funded amount from trainee if he/she did not meet the eligibility criteria.

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