Associate, Risk Data Scientist

TNG Digital Sdn Bhd; Kuala Lumpur; On-site; MYR 60,000 - 90,000; Full time

Job summary

Join TNG Digital Sdn Bhd as an Associate Risk Data Scientist in Kuala Lumpur. You will build ML models for fraud detection, analyze large datasets, and collaborate with engineering, product, and BI teams to deploy risk solutions.

Required to have a bachelor’s in CS/DS/ML, 1+ year in data analysis and modeling, proficiency in Python and SQL, and experience with Looker. Strong communication and problem-solving are essential for influencing decisions.

Qualifications

• Bachelor’s degree in computer science, data science, machine learning, or a related technical field.
• 1 year of experience in data analysis, modeling, and visualization.
• Proficiency in Python and SQL; experience with Looker and ML/algorithm development for fraud detection.

Responsibilities

• Identify, analyze and mitigate fraud risks for TNGD platforms.
• Develop and implement ML models to detect and prevent fraudulent activities.
• Design rules and frameworks to identify risk across products.

Skills

Fraud detection modeling

Data analysis

Communication

Education

Bachelor’s degree in CS/DS/ML

Tools

Python

SQL

Looker

Job description

# Associate, *Risk Data Scientist*Kuala Lumpur, MalaysiaPermanent#### Duties & Responsibilities* A Data Scientist in Fraud Risk typically has responsibilities focused on identifying, analyzing, and mitigating fraud risks for TNGD.* Build Models and Algorithms:* Develop and implement machine learning models and algorithms to detect and prevent fraudulent activities.* Design rules and frameworks to identify and mitigate fraud and credit risks across various products within TNGD platforms.* Data Analysis and Risk Assessment:* Analyze large datasets to uncover patterns, trends, and anomalies that may indicate fraudulent activity.* Utilize statistical methods to assess the risk and impact of potential fraud on the business.* Process Improvement:* Develop and refine processes to root out high-risk activities, ensuring that fraud detection methods are efficient and effective.* Collaboration:* Work closely with cross-functional teams, including engineering, product management, and BI team, to integrate fraud detection tools and strategies.* Innovation and Learning:* Stay updated with the latest trends and advancements in fraud detection and machine learning.* Seek opportunities to innovate and enhance existing fraud prevention techniques.* Reporting and Communication:* Communicate findings and insights to stakeholders through reports and presentations.* Make recommendations based on data-driven insights to influence strategic decisions.#### Requirements* Education:* A bachelor's degree or higher in computer science, data science, machine learning, or a related technical field.* Experience:* A minimum of 1 year of experience in data analysis, modeling, and visualization.* Technical Skills:* Proficiency in programming languages such as Python and SQL.* Experience with data visualization tools like Looker.* Strong skills in machine learning and algorithm development for fraud detection.* Analytical Skills:* Ability to analyze large datasets to identify patterns, trends, and anomalies indicative of fraud.* Soft Skills:* Strong communication skills to effectively present findings and insights to stakeholders.* An act-like-an-owner mentality, showing initiative and responsibility for tasks.