Full Time Senior Data Scientist Jobs, in RiDiK (a Subsidiary Of CLPS. Nasdaq: CLPS) - Maukerja

Position: Senior Data Scientist - Python

Company: RiDiK Pte Ltd

EXP: 3+ Years

Location: Singapore

Job Summary:

A. Educational Qualification & Experience

Education: Degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics or a related quantitative discipline.

Experience: 3+ years of hands-on experience in data science, advanced analytics, model validation, fraud/risk analytics or programme analytics.

B. Technical & Professional Competencies

Strong hands-on proficiency in Python and SQL for data extraction, transformation, exploratory analysis, with experience building reproducible analytical workflows.

Hands-on experience developing, validating or enhancing predictive, risk-scoring, fraud-detection or anomaly-detection models, including feature development, back-testing, threshold calibration and performance evaluation using measures such as precision, recall and related trade-offs.

Experience translating business, policy or operational requirements into analytical specifications, model logic, indicators, rules or measurable risk hypotheses.

Experience working with complex, large-scale datasets, including assessing data quality, tracing data lineage, investigating anomalies and documenting analytical assumptions.

About CLPS RiDiK

RiDiK is a global technology solutions provider and a subsidiary of CLPS Incorporation (NASDAQ: CLPS), delivering cutting-edge end-to-end services across banking, wealth management, and e-commerce. With deep expertise in AI, cloud, big data, and blockchain, we support clients across Asia, North America, and the Middle East in driving digital transformation and achieving sustainable growth. Operating from regional hubs in 10 countries and backed by a global delivery network, we combine local insight with technical excellence to deliver real, measurable impact. Join RiDiK and be part of an innovative, fast-growing team shaping the future of technology across industries