This is a remote position.

We are seeking a Senior Data Scientist to design and deliver advanced analytics and machine learning solutions that drive measurable business value. The role spans the full lifecycle from problem framing and feature engineering to model development, deployment, and monitoring, with a strong focus on explainability, robustness, and operational adoption.

Problem Framing & Solution Design

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Partner with business stakeholders to translate operational problems into analytical and ML use cases

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Define hypotheses, success metrics, and evaluation frameworks

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Identify the right modeling approach (statistical, classical ML, deep learning, optimization)

Model Development & Experimentation

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Perform exploratory analysis, feature engineering, and model selection

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Develop, train, validate, and tune predictive, prescriptive, and generative models

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Apply rigorous experimentation, cross-validation, and bias / fairness checks

MLOps & Productionization

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Work with data and platform engineers to deploy models into production

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Implement monitoring for drift, performance, and data quality

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Contribute to MLOps standards, model registries, and reproducibility practices

Communication & Adoption

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Communicate findings, model behavior, and limitations clearly to non-technical audiences

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Drive adoption of analytical solutions through training, documentation, and stakeholder engagement

Requirements

Technical

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6–10+ years of applied data science / machine learning experience

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Strong proficiency in Python (pandas, scikit-learn, PyTorch or TensorFlow) and SQL

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Hands-on experience across multiple model families, including:

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Regression, classification, and time-series forecasting

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Optimization and operations research methods

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Deep learning and/or modern LLM / generative approaches (a plus)

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Experience deploying models on cloud platforms (AWS SageMaker, Azure ML, Databricks, or equivalent)

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Solid understanding of statistics, experimental design, and causal inference

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Familiarity with MLOps practices and tooling (MLflow, model registries, CI/CD for ML)

Industry / Domain (Highly Preferred)

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Experience in mining, metals, heavy industry, oil & gas, utilities, or other large industrial sectors is a strong plus

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Exposure to predictive maintenance, process optimization, supply chain analytics, geological / exploration data, or sensor / IoT analytics is highly valued

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Prior experience in the GCC or Saudi Arabia is an advantage

Governance & Compliance Awareness

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Awareness of model risk, explainability, and responsible AI principles

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Understanding of data privacy, PII handling, and regulatory considerations

Soft Skills

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Strong storytelling and ability to translate analytics into business impact

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Comfort working directly with senior business stakeholders

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Curious, structured, and pragmatic problem-solver

Education & Certifications

Preferred:

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Degree in Computer Science, Statistics, Mathematics, Engineering, Operations Research, or related quantitative field; advanced degree (MSc / PhD) is a strong advantage

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Relevant cloud or ML certifications are a plus

Additional Requirements

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Onsite presence in Riyadh required

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Experience working in large enterprise or government environments

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Ability to operate in a multi-vendor delivery ecosystem