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Analyst - Data Science

Job in Manama, Bahrain
Listing for: Marsh
Full Time position
Listed on 2026-10-21
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Business Systems & Technology Analysis
Salary/Wage Range or Industry Benchmark: 8000 - 12000 BHD Yearly BHD 8000.00 12000.00 YEAR
Job Description & How to Apply Below
Company:

Marsh

Description:

Analyst - Data Science

Are you a curious, analytical early-career data professional eager to solve business problems with technology and insight? Join Marsh in Bahrain and support countries across India, the Middle East, and Africa by helping transform processes, improve tools, and deliver data-driven solutions. You'll work with colleagues across geographies and gain exposure to data science, AI, visualization, and business analytics in a dynamic, collaborative environment.

About

This Role

This is an exciting opportunity for a developing data science professional to gain hands-on experience in analytical problem-solving, tool development, and business process improvement while contributing to innovative, practical solutions.

Key Responsibilities
  • Explore and understand business needs and nuances across different teams and functions.
  • Extract, analyze, and model data using analytical tools and techniques to improve business processes and create value.
  • Support the development of tools and solutions using Python, AI, Power Apps, Power BI, and Power Automate.
  • Assist in building and delivering end-to-end analytical tools and automation solutions.
  • Apply problem-solving skills to understand business requirements and evaluate potential solution approaches.
  • Demonstrate strong attention to detail in all analysis and deliverables.
  • Support the use of AI tools, including Claude Co-work, and help train others when needed.
  • Collaborate with stakeholders and support reporting and communication requirements.
  • Continuously learn about Marsh, the business unit, and the wider insurance industry.
What We're Looking For
  • 0-2 years of experience in data science, analytics, or related areas.
  • Strong technical understanding of data extraction from different types of documents.
  • Intermediate Microsoft Excel skills.
  • Hands-on experience with Python, including Python Streamlit.
  • Understanding of NLP techniques and pipelines.
  • Fundamental knowledge of LLMs.
  • Strong Microsoft Office skills.
  • Good verbal and written communication skills.
  • Strong problem-solving ability and a proactive, curious mindset.
  • Ability to build stakeholder management and reporting skills over time.
Nice to Have
  • Exposure to AI tools, automation platforms, or dashboarding tools such as Power BI.
  • Experience working on end-to-end tool development or analytical delivery.
  • Interest in business transformation, process improvement, and innovation.

Marsh (NYSE: MRSH) is a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit , or follow us on Linked In and X.

Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, disability, ethnic origin, family duties, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, skin color, or any other characteristic protected by applicable law.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one "anchor day" per week on which their full team will be together in person.

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