Table of Contents
Job Overview
About the Company
Available Jobs
Job Description
What You’ll Actually Build
Who This Role Is Ideal For
Job Responsibilities
Why This Role?
Requirements
How to Apply
FAQs
Job Overview
If you’re searching for a Head of Data Science Dubai role that goes far beyond dashboards and reporting, ClearGrid is hiring a technical leader to build the predictive engine behind a modern AI-driven debt resolution platform. This role is about architecting, building, and deploying systems that turn messy real-world data into models that directly guide capital allocation, portfolio pricing, repayment strategy, and customer outcomes.
ClearGrid describes this position as Head of Data Science & Intelligence—a leader who can translate a massive data ecosystem into self-learning decision systems. You’ll be building models that influence everything from repayment probability and cashflow forecasting to non-performing loan (NPL) purchase strategy and securitization analytics.
Job Title: Head of Data Science & Intelligence (Head of Data Science)
Company Name: ClearGrid
Location: Dubai, United Arab Emirates
Employment Type: Full-time
Work Model: Dubai-based (as per job location; confirm exact schedule during process)
Start Date: As per hiring timeline
Short summary of the opportunity:
You will design predictive models, operationalize ML pipelines, create feature stores for real-time intelligence, and integrate model outputs into business workflows like CRM, call orchestration, and automation—turning data science into an operating system for the company.
About the Company
ClearGrid is a fast-growing startup on a mission to modernize debt resolution using AI, automation, and real-time data. Their approach is positioned as customer-first and compliance-aware, aiming to create better outcomes for both lenders and borrowers through transparency, tailored options, and operational efficiency.
Founded in 2023 with a team of roughly 75 coworkers (as stated in the posting), ClearGrid is building a digital platform that rethinks collections from scratch—using modern data architecture and AI-driven workflows rather than legacy playbooks.
What makes this interesting for senior data science leaders is the scope: collections and debt resolution represent a huge market with a lot of inefficiency. The company frames this as building “the brains” of a large financial platform—meaning your work is expected to influence real decisions, not just reports.
Available Jobs
If you’re considering this opportunity but also want to broaden your search using closely related roles and keywords, these are common adjacent positions in AI-fintech environments:
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Director of Data Science – Fintech – Dubai
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Head of Machine Learning – UAE
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Credit Risk Modeling Lead – Dubai
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MLOps / ML Platform Lead – Dubai
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NLP / Conversation Intelligence Lead – UAE
These roles overlap with ClearGrid’s emphasis on ML productionization, credit analytics, operational decisioning, and AI integration.
Job Description
The Head of Data Science Dubai role at ClearGrid is positioned as a builder-leader job. You will architect data science systems that become a decision engine across the business—driving how borrowers are segmented, how strategies are selected, how outcomes are predicted, and how loan portfolios are priced.
ClearGrid is explicit about what this role is not: it’s not business intelligence, report generation, or passive analysis. It’s a role for someone who can create predictive intelligence that shapes product and operations proactively.
What You’ll Actually Build
Your work will sit at the intersection of machine learning, credit analytics, and operational automation. Examples of the systems you’ll build include:
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Repayment probability and behavioral segmentation models that influence outreach strategy
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PTP likelihood (promise-to-pay) prediction to optimize contact workflows
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Loss-given-default and recovery rate prediction models used for portfolio valuation
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Cashflow forecasting and risk engines for decisioning and capital planning
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Conversation intelligence inputs/outputs aligned with AI agents and LLM modules
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NPL pricing and securitization analytics integrating borrower behavior and macro variables
The real point: you won’t be “supporting the business.” You’ll be creating the intelligence layer the business runs on.
Who This Role Is Ideal For
This role is ideal for a leader who:
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Has shipped real ML systems into production and owned outcomes over time
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Understands credit/finance enough to build models that map to risk and pricing reality
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Can build fast without sacrificing rigor, monitoring, and governance
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Communicates comfortably with both engineers and finance leaders
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Enjoys building end-to-end systems: data → features → model → deployment → feedback loop
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Wants ownership in a high-ambition startup environment with significant greenfield scope
Job Responsibilities
As Head of Data Science & Intelligence, your responsibilities will span modeling, pipelines, systems design, and team practices. Key responsibilities include:
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Architect and build predictive models across segmentation, PTP likelihood, LGD, recovery prediction, and portfolio valuation
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Operationalize ML pipelines using Python, SQL, and modern MLOps frameworks (examples mentioned include Airflow, dbt, TensorFlow, PyTorch or equivalent)
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Design feature stores and data schemas to enable real-time intelligence for AI voice agents, dashboards, and risk engines
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Build and fine-tune models for securitization and NPL pricing, incorporating macroeconomic signals, borrower behavior, and cashflow projections
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Integrate AI/ML outputs into business operations, connecting models into CRM, call orchestration, and workflow automation
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Collaborate with AI engineers to align model I/O structures with LLM systems and conversation intelligence modules
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Own the full model lifecycle: data prep, modeling, validation, deployment, monitoring, and retraining with human-AI feedback loops
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Develop behavioral segmentation frameworks that dynamically group borrowers by risk, responsiveness, and emotional tone
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Create financial intelligence systems bridging data science and finance for loan book pricing, debt sale structuring, and securitization analytics
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Mentor analysts and data engineers, setting standards for version control, documentation, code review, and model governance
This is a role where “responsibilities” translate into systems that either run smoothly in production—or fail publicly. ClearGrid is clearly hiring for the former.
Why This Role?
A Head of Data Science role is only exciting if it has leverage. This one has leverage in multiple directions: finance impact, product impact, operational impact, and platform impact.
1) You’re building the decision engine, not reporting on it
ClearGrid frames this as building intelligence that directly moves capital and shapes strategy. If you’ve been stuck in analytics-only environments, this is a clear step into decisioning and automation.
2) Massive modeling surface area with real-world feedback loops
You’ll have access to live signals: customer behavior, contact outcomes, repayment patterns, operational performance, and agent interactions. That creates a strong loop for iterative improvement—especially when you own monitoring and retraining.
3) Unique blend: credit analytics + AI operations + NLP intelligence
Few roles let you combine classic credit risk modeling (LGD, recovery, pricing) with modern systems like AI voice agents and conversation intelligence. That combination is rare and highly valuable long-term.
4) Startup pace with high technical ambition
You’re joining a company that describes itself as building from scratch with modern tools. That implies speed, ownership, and fewer legacy constraints—ideal for builder-type leaders.
5) Career credibility in Dubai’s fast-growing fintech ecosystem
Dubai is increasingly a hub for fintech and AI-first financial infrastructure. Leading data science at a startup tackling a complex financial category can be a strong platform for future VP/Chief Data roles.
Requirements
To be considered strongly for this Head of Data Science Dubai role, ClearGrid highlights the following:
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Experience: 6–10+ years in data science or quantitative modeling (fintech, credit, or analytics-heavy startups preferred)
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Production coding: Expert in Python and SQL with production-level coding, experimentation, and debugging skills
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Modeling depth: Strong ML foundations plus probabilistic modeling, NLP, and predictive analytics
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Deployment experience: Proven ability to deploy ML models to production (examples include MLflow, Vertex AI, SageMaker, or custom pipelines)
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Finance/credit familiarity: Comfort with credit analytics and financial modeling including portfolio risk, pricing, and securitization concepts
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Data architecture: Experience with warehouses (BigQuery, Snowflake), orchestration (Airflow, Prefect), and data versioning (dbt, Git)
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Messy data mastery: Ability to transform raw, inconsistent data into structured, usable systems
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Feedback loops: Experience building human-in-the-loop or human-AI feedback systems that improve models and decisions over time
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Bonus: Exposure to LLM integration, embeddings, and model alignment methods
How to Apply
To apply for the Head of Data Science role at ClearGrid in Dubai:
FAQs
1) Is this Head of Data Science Dubai role focused on dashboards or BI?
No. The role is explicitly positioned as building predictive intelligence systems, not dashboards or report generation.
2) What kind of models will I build at ClearGrid?
Expect models for segmentation, PTP likelihood, loss-given-default, recovery prediction, portfolio valuation, cashflow forecasting, and NPL pricing—plus conversation intelligence integrations.
3) Do I need fintech or credit experience?
It’s strongly preferred. ClearGrid highlights fintech/credit as ideal backgrounds because the role includes portfolio risk, pricing, and securitization concepts.
4) What tools and frameworks are relevant?
Python and SQL are core. The posting references Airflow, dbt, TensorFlow/PyTorch, and production deployment tooling like MLflow/Vertex AI/SageMaker or equivalents.
5) Is this role more research-focused or engineering-focused?
It’s both, but delivery is crucial. ClearGrid describes the ideal candidate as a builder-scientist hybrid—research mindset with engineering-grade execution.