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āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāđƒāļŠāđ‰āļ„āļģāļŦāļĨāļąāļ

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāļŦāļĄāļ§āļ”āļŦāļĄāļđāđˆāļ‡āļēāļ™

āđ€āļĨāļ·āļ­āļāļŦāļĄāļ§āļ”āļŦāļĄāļđāđˆāļ‡āļēāļ™

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāļ›āļĢāļ°āđ€āļ āļ—āļ˜āļļāļĢāļāļīāļˆ

āđ€āļĨāļ·āļ­āļāļ›āļĢāļ°āđ€āļ āļ—āļ˜āļļāļĢāļāļīāļˆ

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāļŠāđˆāļ§āļ‡āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™

āļ•āļąāđ‰āļ‡āđāļ•āđˆ
āļ–āļķāļ‡

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāļŠāļ·āđˆāļ­āļšāļĢāļīāļĐāļąāļ—

āļžāļīāļĄāļžāđŒāļŠāļ·āđˆāļ­āļšāļĢāļīāļĐāļąāļ—

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāļĢāļ°āļ”āļąāļšāļ•āļģāđāļŦāļ™āđˆāļ‡āļ‡āļēāļ™

āļ„āđ‰āļ™āļŦāļēāđ‚āļ”āļĒāļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™

āđāļŠāļ”āļ‡āļœāļĨ 1 - 4 āļ•āļģāđāļŦāļ™āđˆāļ‡āļ‡āļēāļ™ āļˆāļēāļāļ—āļąāđ‰āļ‡āļŦāļĄāļ” 4 āļ•āļģāđāļŦāļ™āđˆāļ‡āļ‡āļēāļ™
āļ—āļĩāđˆāļĄāļĩāļ„āļģāļ§āđˆāļē Hive
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āļ­āļąāļžāđ‚āļŦāļĨāļ”āđ€āļĢāļ‹āļđāđ€āļĄāđˆāļ‚āļ­āļ‡āļ„āļļāļ“ AI āļ‚āļ­āļ‡āđ€āļĢāļēāļˆāļ°āļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđāļĨāļ°āđāļ™āļ°āļ™āļģāļ•āļģāđāļŦāļ™āđˆāļ‡āļ‡āļēāļ™āļ—āļĩāđˆāļ”āļĩāļ—āļĩāđˆāļŠāļļāļ”āđƒāļŦāđ‰āļ„āļļāļ“
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ€āļ­āļīāļ™āļŠāđŒāļ— āđāļ­āļ™āļ”āđŒ āļĒāļąāļ‡ 1
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ€āļ­āļīāļ™āļŠāđŒāļ— āđāļ­āļ™āļ”āđŒ āļĒāļąāļ‡ 1

āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒ:

6 āļ›āļĩāļ‚āļķāđ‰āļ™āđ„āļ›

āļ—āļąāļāļĐāļ°:

Big Data, Good Communication Skills, Scala

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • Collate technical and functional requirements through workshops with senior stakeholders in risk, actuarial, pricing and product teams.
  • Translate business requirements to technical solutions leveraging strong business acumen.
  • Analyse current business practice, processes, and procedures as well as identifying future business opportunities for leveraging Data & Analytics solutions on various platforms.
10 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ„āļ—āļĒāļ­āļ­āļĒāļĨāđŒ 2
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āđ„āļ—āļĒāļ­āļ­āļĒāļĨāđŒ 2
āļĻāļĢāļĩāļĢāļēāļŠāļē, āļŠāļĨāļšāļļāļĢāļĩ, āļšāļĢāļīāļŦāļēāļĢāļœāļĨāļīāļ•āļ āļąāļ“āļ‘āđŒ / āļšāļĢāļīāļŦāļēāļĢāđāļšāļĢāļ™āļ”āđŒāļŠāļīāļ™āļ„āđ‰āļē āļšāļĢāļīāļŦāļēāļĢāļœāļĨāļīāļ•āļ āļąāļ“āļ‘āđŒ / āļšāļĢāļīāļŦāļēāļĢāđāļšāļĢāļ™āļ”āđŒāļŠāļīāļ™āļ„āđ‰āļē

āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒ:

5 āļ›āļĩāļ‚āļķāđ‰āļ™āđ„āļ›

āļ—āļąāļāļĐāļ°:

Data Analysis, Automation, Python

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • Work with stakeholders throughout the organization to understand data needs, identify issues or opportunities for leveraging company data to propose solutions for support decision making to drive business solutions.
  • Adopting new technology, techniques, and methods such as machine learning or statistical techniques to produce new solutions to problems.
  • Conducts advanced data analysis and create the appropriate algorithm to solve analytics problems.
5 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļšāļīāđŠāļāļ‹āļĩ 3
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļšāļīāđŠāļāļ‹āļĩ 3

āļ—āļąāļāļĐāļ°:

Data Analysis, ETL, Data Warehousing

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

  • Data Architecture: Design, develop, and maintain the overall data architecture and data pipeline systems to ensure efficient data flow and accessibility for analytical purposes.
  • Data Integration: Integrate data from multiple sources, including point-of-sale systems, customer databases, e-commerce platforms, supply chain systems, and other relevant data sources, ensuring data quality and consistency.
  • Data Modeling: Design and implement data models that are optimized for scalability, ...
11 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļšāļĢāļīāļĐāļąāļ— āļ•āļīāđŠāļāļ•āđŠāļ­āļ āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļŠāđŒ āļˆāļģāļāļąāļ” 4
āļŦāļēāļ‡āļēāļ™ āļŠāļĄāļąāļ„āļĢāļ‡āļēāļ™ āļšāļĢāļīāļĐāļąāļ— āļ•āļīāđŠāļāļ•āđŠāļ­āļ āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļŠāđŒ āļˆāļģāļāļąāļ” 4

āļ›āļĢāļ°āđ€āļ āļ—āļ‡āļēāļ™:

āļ‡āļēāļ™āļ›āļĢāļ°āļˆāļģ

āđ€āļ‡āļīāļ™āđ€āļ”āļ·āļ­āļ™:

āļŠāļēāļĄāļēāļĢāļ–āļ•āđˆāļ­āļĢāļ­āļ‡āđ„āļ”āđ‰

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18 āļ§āļąāļ™āļ—āļĩāđˆāļœāđˆāļēāļ™āļĄāļē
āļ”āļđāđ€āļžāļīāđˆāļĄāđ€āļ•āļīāļĄkeyboard_arrow_down
āļŠāđˆāļ‡āđāļˆāđ‰āļ‡āđ€āļ•āļ·āļ­āļ™āļ‡āļēāļ™āđƒāļŦāļĄāđˆāļĨāđˆāļēāļŠāļļāļ”āļŠāļģāļŦāļĢāļąāļšHive
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