What You'll Do:

Partner with business teams to understand challenges, clarify objectives, and define analytically sound problem statements. Translate business needs into actionable data science projects.
Clean, preprocess, and transform structured and unstructured data. Engineer features that improve model performance and integrate multiple data sources for comprehensive analysis.
Build predictive, classification, clustering, or other machine learning models. Evaluate performance, iterate based on results and stakeholder feedback, and ensure models meet business objectives.
Present findings through clear narratives, dashboards, and interactive tools. Translate complex analytical results into actionable recommendations for decision-making.
Design intuitive dashboards, visualizations, and self-service analytics tools to help teams monitor metrics, explore data, and act on insights.
Collaborate with engineering teams to operationalize models. Monitor performance, recommend enhancements, and support iterative improvement in production workflows.

What We're Looking For:

Strong analytical skills with the ability to convert business questions into data-driven solutions.
Proficiency in Python, R, SQL, and libraries such as pandas, scikit-learn, or equivalents.
Solid foundation in statistics, probability, hypothesis testing, and exploratory data analysis.
Experience building and validating machine learning models using modern frameworks.
Familiarity with data engineering concepts, including data lakes, warehouses, marts, REST APIs, and big data tools (Spark, Hadoop, Kafka).
Expertise in data visualization tools and frameworks such as Tableau, Power BI, Plotly, or custom dashboards.
Strong communication skills, capable of conveying insights to both technical and non-technical audiences.
Collaborative mindset, highly organized, and comfortable working in Agile environments with multiple priorities.

Qualifications & Experience:

Degree or equivalent experience in Data Science, Statistics, Computer Science, Engineering, Mathematics, or related fields.
Proven experience managing end-to-end data science projects-from scoping and data prep to modeling, visualization, and deployment.
Prior experience working with cross-functional teams and stakeholders in a fast-paced, iterative environment.
Hands-on experience with production-grade machine learning workflows is a plus.

Interested candidates are encouraged to submit their resumes outlining their relevant experience and achievements to apply88(@)talentvis.comor click apply!

..We regret to inform that only shortlisted candidates would be notified..

EA License No: 04C3537

EA Personnel No: R22106683

EA Personnel Name: Yang Hui Shan, Sherri

UAT Tester (Local Bank) (12 months) #JTL

Data Scientist

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