MetLife

Overview of the role

MetLife is a purpose-driven company. “Always with you, building a more confident future” is our anchor, our North star, our reason for being. Everything we do traces back to Our Purpose.

MetLife is embarking on an exciting new chapter – our New Frontier strategy – focused on delivering sustainable growth through innovation, customer-centricity and operational excellence.

As a global leader in insurance and financial services, we are leveraging advanced analytics, digital platforms, and AI to re-imagine how we serve millions of customers around the world.

As a Data Scientist at MetLife Gulf, you won’t just be building models – you’ll be shaping the future. You will be a key driver in our transformation into a data-first, insights-led organization, helping us unlock new value across customer experience, risk management, product innovation and business optimization.

You’ll be joining the Gulf Data Analytics team, a unit at the heart of our data transformation in Gulf, and which is evolving to play a pivotal role in translating data into strategic impact for our Gulf business – bringing fresh thinking, local insights, and advanced modelling techniques to the forefront of business decisions.

This role reports to the Head of Data Analytics - Gulf, and it’s an opportunity to join a founding team and contribute to shaping the data science culture from the ground up and solving complex problems for diverse lines of business.

Responsibilities

• Responsible for the conception, planning, and prioritizing of data science projects.
• Responsible for building analytic systems and predictive models as well as experimenting with new models and techniques.
• Support the Head of Data Analytics with setting the data science strategical direction and roadmap; Ensure that data science projects align with organizational goals.
• Support and working closely with the Data Consumption Unit (Intelligence and Reporting Function):
  1. Interact with business stakeholders and subject matter experts to understand their data visualization and business intelligence needs.
  2. Design, develop, test, and deploy Power BI scripts and generate visually appealing and insightful reports.
  3. Integrate Power BI reports into other applications to provide enhanced business capabilities.
  4. Create custom visualization and implement row level security on data.
  5. Build data models and develop dashboards using Power BI desktop.
  6. Develop tabular and multidimensional models that are compatible with warehouse standards.
  7. Use advance level calculations on the data set using DAX functions in Power BI.
• Contribute to deploying solutions across data stack: backend data pipelines and modelling frontend dashboards.
• Teach, lead, and counsel colleagues on new techniques or solutions
  1. Directly engage with stakeholders: understand and address requirements
  2. Coaching: growing the data intelligence and reporting team into an advanced analytics /data science capable team.
  3. Collaborate with team to develop innovative solutions to complex business problems.
  4. Collaborate with data and software engineers to enable deployment of sciences and technologies that will scale across the company’s ecosystem.
• Lead data mining and collection procedures
  1. Design and build efficient data pipelines to train, test and implement quality and scalable ML, gen (AI) models /solution.

Qualifications & Experiences

• Masters is preferred but bachelor’s degree in quantitative field like Computer Science, Data Engineering, Mathematics, or related field.
• 3+ years in a similar role with hands on experience solving complex Machine Learning and Deep Learning problems.
• Experience building predictive modeling in the insurance industry (Pricing, Claims, Sales, etc.).
• Proficiency in database administration.
• Python/R programming with experience in building data pipelines.
• Microsoft Azure experience is a plus.
• The candidate must have expertise in natural language processing, machine learning, conceptual modeling, statistical analysis, predictive modeling, and hypothesis testing. They should also be skilled in using dashboard and visualization tools like Power BI and Alteryx.
• Effective communication: be able to connect with the team and convey information clearly.
• Storytelling: strong data visualization skills and the ability to explain technical solutions simply to a non-technical audience.
• Business Acumen: the candidate must possess a strong business mindset, demonstrating the ability to swiftly identify risks and opportunities, as well as generate innovative solutions to business challenges.