Data Scientist
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About the Role
Welcome to where every role drives real change. At Everbridge, we don't just offer jobs, we offer the chance to shape industries and transform communities. Join professionals who wake up knowing their work matters, solving challenges that impact millions.
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Overview
Welcome to where every role drives real change.
At Everbridge, we don't just offer jobs, we offer the chance to shape industries and transform communities.
Join professionals who wake up knowing their work matters, solving challenges that impact millions.
Whether leading breakthrough initiatives or starting your journey, you'll work on projects that leave a lasting legacy.
Every decision, every idea here creates ripple effects that matter.
Ready to do work that matters?
Explore our roles and join those making a real difference.
Description
Everbridge, a leading financial technology company based in Riyadh, Saudi Arabia, is seeking a Data Scientist to join our team and help build the quantitative backbone of our underwriting, operations, and growth functions.
In this role, you will translate complex platform data into the insights and models that shape capital allocation, risk appetite, and strategic decision-making across the business.
You will be responsible for developing predictive models across areas such as payment Behavior, portfolio analytics, and buyer segmentation, while partnering with cross-functional stakeholders to embed data-driven thinking into day-to-day operations.
As a Data Scientist at Everbridge, you will contribute to high-impact projects that influence how capital moves through our platform, and play a meaningful role in shaping the future of financial technology in the region.
Requirements
- Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field.
- 3+ years of experience in data analysis and modelling, including demonstrated experience — through internships or research.
- Strong proficiency in Python (pandas, scikit-learn, PyTorch or TensorFlow) and SQL; familiarity with R or similar languages is a plus.
- Hands-on experience with machine learning algorithms, frameworks, and tooling across the full model lifecycle.
- Working knowledge of credit risk, time-series forecasting, or causal inference is highly desirable.
- Strong analytical and problem-solving skills, with the ability to structure ambiguous problems and translate them into quantitative solutions.
- Excellent communication skills, with the ability to convey quantitative findings clearly to both technical and non-technical stakeholders.
Roles And Responsibilities
- Design, build, validate, and deploy predictive models for buyer payment behaviour, default risk, and portfolio performance.
- Analyse large and complex datasets to identify trends, patterns, and actionable insights that support business objectives.
- Develop features, dashboards, and analytical tools that empower Credit, Operations, and Commercial teams to make data-driven decisions.
- Partner with the Credit and Risk function to quantify exposure, concentration, and early-warning signals across the portfolio.
- Collaborate with Engineering to productionise models, ensuring robust governance, monitoring, and explainability standards.
- Contribute to product analytics, including onboarding funnels, cohort analysis, buyer segmentation, and unit economics.
- Present findings and recommendations to stakeholders across technical and non-technical audiences in a clear and compelling manner.
- Stay current with advancements in data science, machine learning, and applied AI, bringing relevant techniques into the team's toolkit.
Benefits
- Competitive salary package
- Health insurance coverage
- Opportunities for professional growth
- Supportive work environment
- Paid leave and holidays
Skills
- Strong statistical and analytical skills.
- Proficiency in data visualization tools like Tableau or Power BI.
- Excellent communication and presentation skills.
- Ability to work independently and as part of a team.
- Knowledge of cloud platforms such as AWS or Azure is a plus.
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