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Machine Learning Engineer (Risk) Job Opening In Singapore, Singapore – Now Hiring SHIELD


Job description

SHIELD is a device-first fraud intelligence platform that helps digital businesses worldwide eliminate fake accounts and stop all fraudulent activity.

Powered by SHIELD AI, we identify the root of fraud with the global standard for device identification (SHIELD Device ID) and actionable fraud intelligence, empowering businesses to stay ahead of new and unknown fraud threats.

We are trusted by global unicorns like inDrive, Alibaba, Swiggy, Meesho, TrueMoney, and more.

With offices in LA, London, Jakarta, Bengaluru, Beijing, and Singapore, we are rapidly achieving our mission - eliminating unfairness to enable trust for the world.

Responsibilities

As a Machine Learning Engineer (Risk), you will develop and leverage innovative machine learning solutions to solve complex sets of problems and applications.

By analyzing and detecting patterns in vast amounts of data, you will have a good understanding of machine learning life cycle-algorithms, data structures and design patterns.

We are looking for talented and passionate individuals who are proactive in identifying problems and have the logical thought process and skills to solve them.

There will be many opportunities to explore new tech stacks and to work on advanced technologies.

  • Ability to design and develop machine learning algorithms
  • Discover, design, and develop analytical methods to support novel approaches of data and information processing
  • Identify and apply appropriate methods to process and analyze large data-sets of labelled and unlabeled records, and discover new valuable insights for the system
  • Provide support on other part of the system (not limited to Machine Learning)
  • Conduct software performance analysis, scaling, tuning and optimization
  • Review and contribute to improve current software and system architecture for stability and to optimize performance
  • Research & development of fraud detection solution

Qualifications

  • Minimum Bachelor Degree in Computer Science, Information System with Machine Learning specialization or equivalent
  • Strong foundation in database and data scaling
  • Experience with various Machine Learning algorithms and ability to apply in real life cases
  • Experience in MySQL, NoSQL and Columnar database
  • Experience in C++, C, Python and other programming languages will be an advantage
  • Prior experience in e-payments or e-commerce industry is a plus
  • Strong analytical, interpersonal, communication and presentation skills
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Required Skill Profession

Engineering


  • Job Details

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Unlock Your Machine Learning Potential: Insight & Career Growth Guide


Real-time Machine Learning Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for Machine Learning in Singapore, Singapore, highlighting market share and opportunities for professionals in Machine Learning roles.

1468 Jobs in Singapore
1468
1308 Jobs in Singapore
1308
Download Machine Learning Jobs Trends in Singapore and Singapore

Are You Looking for Machine Learning Engineer (Risk) Job?

Great news! is currently hiring and seeking a Machine Learning Engineer (Risk) to join their team. Feel free to download the job details.

Wait no longer! Are you also interested in exploring similar jobs? Search now: .

The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at SHIELD adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying Singapore laws and regulations

What Is the Average Salary Range for Machine Learning Engineer (Risk) Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Singapore. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

What Are the Key Qualifications for Machine Learning Engineer (Risk)?

Key qualifications for Machine Learning Engineer (Risk) typically include Engineering and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

How Can I Improve My Chances of Getting Hired for Machine Learning Engineer (Risk)?

To improve your chances of getting hired for Machine Learning Engineer (Risk), consider enhancing your skills. Check your CV/Résumé Score with our free Tool. We have an in-built Resume Scoring tool that gives you the matching score for each job based on your CV/Résumé once it is uploaded. This can help you align your CV/Résumé according to the job requirements and enhance your skills if needed.

Interview Tips for Machine Learning Engineer (Risk) Job Success

SHIELD interview tips for Machine Learning Engineer (Risk)

Here are some tips to help you prepare for and ace your Machine Learning Engineer (Risk) job interview:

Before the Interview:

Research: Learn about the SHIELD's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

Be Honest: Don't exaggerate your skills or experience.

Be Positive: Focus on your strengths and accomplishments.

Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Machine Learning Engineer (Risk) interview at SHIELD, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the SHIELD's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

How to Set Up Job Alerts for Machine Learning Engineer (Risk) Positions

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