Data Scientist Analyst - WFO - Jakarta (ID: 708201)

• Position : Data Scientist Analyst
• Location : Jakarta

Role Summary & Responsibility

Discuss with clients to confirm KPI definitions, event taxonomy, segmentation logic, and data quality expectations; document definitions and assumptions clearly

Coordinate data requests, ingestion specifications, secure transfer requirements, and validation steps; troubleshoot gaps and inconsistencies with client data owners

• Analyze data using statistical software (e.g., Python, R)
• Extract and aggregate data from large sets using SQL, Hive, Spark and other tools
• Deploy and support predictive modeling packages and monitor and calibrate production models
• Solve problems with innovative data science techniques
• Collaborate with data science colleagues and other Visa teams to provide insights to clients.
• Automate and create repeatable analyses or self-service tools
• Ensure timely project delivery to meet business needs
• Promote data innovations and analytics education within Visa
• Optimize code for critical business processes
• Design and develop dashboards using software like Tableau or Power BI
• Communicate complex concepts clearly and effectively
• Collect and report market information and intelligence (marketing trends and competitive products and pricing).

Requirement

Degree (Masters or Ph.D. would be an advantage) in Quantitative field such as Statistics, Mathematics, Physics, Computer Science, Economics, or engineering or equivalent experience

6+ years of professional work experience preferably in banking, payments, fintech, or a related industry.

Hands-on experience with data analytics/programming tools such as Python, R and advanced skills in querying using SQL or other query languages.

Hands-on experience working in Big Data ecosystems such as Hadoop, Spark, Hive, Kafka, GCP, AWS, and Azure. Experience with both on-prem and cloud environments is a plus.

Hands-on experience with BI tools such as Power BI and Tableau.

Proficiency in statistical techniques: Neural Networks, Gradient Boosting, Linear & Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Clustering, Principal Component Analysis, Factor analysis, etc.

Demonstrated experience in planning, organizing, and managing multiple and concurrent analytics projects with diverse cross-functional stakeholders

Strong internal team and external client stakeholder management with a collaborative, diplomatic, and flexible style; able to work effectively in a matrixed organization

• Excellent presentation and storytelling skills, including strong oral and written capabilities
• Storyboarding and data storytelling including strong Excel and PowerPoint skills