Data Scientist, Digital Transformation Project

Zenith-Infotech

Singapore

On-site

SGD 70,000 - 120,000

Full time

9 days ago

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Job summary

Zenith Infotech Pte Ltd. is seeking a data science professional to design, develop, and deploy data science products including dashboards, reports, and ML models in an agile setting.

You will engage stakeholders to translate business questions into analytical hypotheses and drive end-to-end analytics from data audits to model deployment. Responsibilities include building data pipelines, feature engineering, model training and evaluation, and delivering interactive dashboards using Qlik Sense,

Qualifications

  • Proven track record translating business problems into analytical solutions with measurable impact.
  • Strong hands-on experience in ML, statistical modelling, and data mining on large datasets.
  • Strong knowledge of data warehousing, data modelling, and ETL concepts.
  • Must be able to obtain security clearance due to project sensitivity.

Responsibilities

  • Design, develop, and deploy data science products—dashboards, reports, and ML models.
  • Engage stakeholders to translate business questions into analytical hypotheses.
  • Perform data audits, EDA, and feasibility assessments for AI/ML use cases.
  • Develop data pipelines and databases to support analytics and ML.
  • Build, train, validate, and deploy ML models on large datasets.
  • Develop dashboards and storytelling using Qlik Sense / Power BI / Tableau.
  • Optimize model/data pipeline performance and troubleshoot issues.
  • Conduct code reviews, model validation, and user acceptance testing.
  • Support technical refreshes, retraining, migration, and regression testing.
  • Conduct user training and product demonstrations.

Skills

Python
SQL
Data visualization
ETL
Cloud platforms
Machine learning

Tools

Informatica
Talend

Job description

About the Project:

Digital transformation initiative leveraging cloud, data analytics, and AI to build next-gen data products.

Role:
  • Work in an agile product team under Product Manager to design, develop, and deploy data science products - dashboards, reports, and machine learning models.
  • Engage stakeholders to gather requirements and translate business questions into analytical hypotheses and data science problem statements.
  • Perform data audits, exploratory data analysis (EDA), and feasibility assessments for AI/ML use cases.
  • Design and develop data pipelines, feature engineering workflows, and database models to support analytics and ML.
  • Build, train, validate, and deploy ML / statistical models on large-scale structured and unstructured datasets.
  • Develop interactive dashboards and visual storytelling using Qlik Sense / Power BI / Tableau.
  • Optimize model performance, data pipeline performance, and troubleshoot issues.
  • Perform code reviews, vulnerability checks, model validation, and UAT with end users.
  • Support tech refresh - model retraining, platform migration, regression testing, and code retrofitting.
  • Conduct user training, product demonstrations, and knowledge transfer.
Requirements:
  • Minimum 1 end-to-end project delivered in Scrum / Agile environment.
  • Proven track record translating business problems into analytical solutions with measurable business impact.
  • Strong hands-on experience in machine learning, statistical modelling, and data mining on large datasets.
  • Strong knowledge of data warehousing, data modelling, and ETL concepts.
  • Hands-on experience with:
  • SQL for data querying and analysis
  • Python or R for AI/ML development (e.g. pandas, scikit-learn, TensorFlow, PyTorch)
  • Data visualization: Qlik Sense, Power BI, or Tableau
  • ETL / Data Prep tool: Informatica, Talend, or equivalent.
  • Experience with model evaluation, performance tuning, and troubleshooting.
  • Familiarity with cloud platforms, code quality practices, and UAT
  • Must be able to obtain security clearance due to project sensitivity.
  • Good communication, able to explain complex models to non-technical stakeholders.

Appreciate the interest of all applicants; however only shortlisted candidates will be notified.

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