Data Science and Analytics Manager - Hybrid

Data Science and Analytics Manager - Hybrid

  • Location

    Singapore, Singapore

  • Sector:

    Information Technology

  • Job type:


  • Salary:

    S$8000 - S$12000 per annum

  • Contact:

    Anju Lagah

  • Contact email:


  • Job ref:


  • Published:

    6 months ago

  • Expiry date:


  • Consultant:


Data Science and Analytics Manager - Hybrid

  • Global MNC
  • Part of global Data Science and Analytics team in Singapore, at the heart of the strategy making with ability to influence
  • Working for an organisation that is committed to evolving their business through data intelligence

Job Scope

This role will focus on the development of algorithmic powered solutions in the areas of Net Revenue Management (NRM) and Route-To-Market (RTM) products. The role will be expected to blend the expertise of Data Engineering, Business Intelligence and Data Science to design, source and develop data models to fuel analytics and business intelligence platform.

You will have the experience and ability to quickly understand the business context and problem, apply advanced mathematics and/or statistics to large data sets; and operate in cloud-based environments where data, models, and user interfaces reside in the same platforms-core technologies.

You should thrive in working with both technical teams and commercial business teams.

The position will be both an individual contributor and manager role

Key accountabilities:

Partner with the global and in-market data experts to discover and derive value from connecting external and internal data sources.

Build (ETL) new and evolve data models and pipelines to power algorithmic based Business Intelligent solutions that addresses business problems requiring descriptive, diagnostic, predictive, and/or prescriptive analytics for pricing, promotion, trade spending, assortment, and sales performance management.

Translates the algorithms and analytic models into data models as business needs evolves on a going basis after they are put into production.

Develop a roadmap that scales existing and new data models, to support the portfolio of solutions.

Expand into Business Intelligence solution development focused on automation and scale up of solutions.

Experience and qualifications required:

Professional Skills

  • Analytics Modelling and Techniques Fully Operational
  • Analytic Platforms Working Knowledge
  • Data Exploitation Fully Operational
  • Platform Technology Working Knowledge
  • Data Visualisation Fully Operational

Strong communication skills and ability to work with peers and demonstrate vertical and lateral influence.

Strong track record in solving analytical problems using quantitative and statistical approaches

Relevant Experience:

  • S. or M.S. in a relevant technical field (Operations Research, Computer Science, Statistics, Business Analytics, Econometrics, or Mathematics). Overall commercial experience of 5+ years
  • Ability to manipulate and analyse complex, high-volume, high-dimensionality data from varying sources (Nielsen, SAP, Retailer ePOS; both structured and non-structured data)
    • Experienced knowledge working with large data sets, experience working with distributed computing tools a plus (Map/Reduce, Hadoop, Hive)
    • Experienced knowledge working in Microsoft Azure and applying Cortana to develop scaled analytic models in the cloud
    • Experienced knowledge with relational and columnar databases - SQL is a plus
  • Understanding of Data Mining, Data Modelling, and Data Provisioning (acquisition, transformation and sharing). Demonstrated ability in solution is a plus.
  • Expert knowledge of an analysis tool such as Microsoft PowerBI, and Tableau
  • Proficiency in Python, and preferably in one other language like R, Scala, Java, Golang etc.

Please send your resume in WORD format by clicking the apply button below or contact Anju Lagah on +65 6701 1504 for a confidential discussion. Please note that only short-listed candidates will be contacted.CEI Reg. Number R1219693 (Anju Lagah).