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Data Scientist

Job in Khobar, Eastern Province, Saudi Arabia
Listing for: Wisayah Investment Company
Full Time position
Listed on 2026-07-11
Job specializations:
  • IT/Tech
    Business Systems/ Tech Analyst, AI Engineer (Applied/Software), Data Analyst, IT Business Analyst
Salary/Wage Range or Industry Benchmark: 180000 - 300000 SAR Yearly SAR 180000.00 300000.00 YEAR
Job Description & How to Apply Below

Role Description

The Data Scientist Senior Analyst plays a key role in embedding advanced analytics and AI-enabled capabilities into day-to-day investment and operational workflows. The role combines business-facing enablement with hands‑on solution development—working across teams to improve how data is used, decisions are made, and processes are executed.

The position begins with a strong focus on understanding the firm’s data ecosystem and internal workflows and evolves into designing and building scalable solutions—from workflow automation to more advanced, model-driven applications that support the firm’s broader digital transformation.

Responsibilities
1. Enablement & Use‑Case Development
  • Partner with teams across front, middle, and back office to identify where automation and AI can improve real workflows.
  • Guide business teams in designing and adopting their own enhanced workflows, providing hands‑on support, frameworks, and review.
  • Structure business problems into clearly defined use cases, including requirements, prioritization, and expected impact.
  • Maintain and track a centralized pipeline of initiatives, including progress, adoption, and outcomes (e.g., efficiency gains, quality improvements).
2. Solution Development & Automation
  • Design and build practical solutions that enhance workflows, including automation, data‑driven tools, and intelligent assistants.
  • Develop and deploy AI-supported applications (e.g., agents, document/query solutions) with appropriate controls and reliability considerations.
  • Support implementation of retrieval and knowledge‑access solutions that make internal data and content more usable.
  • Integrate solutions with internal systems and support end‑to‑end automation of recurring processes.
3. Data Landscape & Foundations
  • Build a deep understanding of the firm’s data architecture, including internal systems, vendor platforms, and document repositories.
  • Map key data sources and flows to ensure solutions are grounded in what the data can support.
  • Identify and help address gaps in data accessibility, quality, and structure that impact analytics and automation use cases.
4. Stakeholder & Delivery Management
  • Act as a bridge between business stakeholders and technical or external partners.
  • Support delivery and implementation efforts through hands‑on involvement, review, and coordination.
  • Contribute to evaluation and onboarding of new tools and platforms, including initial assessment of data handling considerations.
5. Continuous Development & Innovation
  • Stay up to date with developments in investment management, data, and applied AI.
  • Contribute to evolving the firm’s capabilities by progressively taking on more advanced technical and solution‑building responsibilities.
Skills
  • Investment Management
  • Business & Use‑Case Structuring
  • Data Analysis & Automation
  • Workflow Optimization
  • Stakeholder Management
  • Communication
  • Applied AI / Emerging Technologies
Requirements
  • Bachelor’s or master’s degree in finance, Economics, Business, Computer Science, Management Information System or a related field.
  • 4–7 years of experience combining investment domain knowledge with hands‑on analytics, automation, or AI-related work.
  • Proven ability to deliver practical solutions (e.g., automation, reporting tools, intelligent workflows) that are adopted by end users.
  • Strong ability to translate between business needs and technical requirements.
  • Familiarity with tools such as SQL, Python, or similar; experience working with data-driven workflows is preferred.
  • Strong communication skills and experience working across cross-functional teams.
  • High ownership mindset, with comfort operating in evolving and ambiguous environments.
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