Senior Data Scientist

Parser

. Design, train, and validate predictive and optimization models using classical ML, statistical modeling, and deep learning architectures .

Posted 10/27/2026contractRemote • SerbiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing predictive and optimization models using advanced machine learning techniques, with a strong focus on AWS deployment and MLOps practices. Proficient in translating complex data initiatives into actionable insights for business impact.

Highest-signal resume keywords

Machine Learning Lifecycle ManagementAWS Deployment (SageMaker, Lambda, ECS)Deep Learning Frameworks (PyTorch, TensorFlow)Statistical Inference and Experimental DesignModel Interpretability Frameworks (SHAP, LIME)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Python (Pandas, NumPy, Scikit-learn)SQL QueryingMLOps PracticesA/B Testing FrameworksData Drift MonitoringConcept Drift MonitoringStatistical ModelingPredictive ModelingOptimization ModelsGenerative AI Workflows

Soft Skills

CollaborationCommunicationInfluencing StakeholdersProblem-SolvingStrategic Thinking

Industry Keywords

Data ScienceAdvanced AnalyticsComputer VisionNatural Language ProcessingQuantitative Discipline

Tech Stack

Tools & technologies

AWSCloudNumpyPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Design, train, and validate predictive and optimization models using classical ML, statistical modeling, and deep learning architectures
Own the end-to-end ML lifecycle on AWS using SageMaker, Lambda, and ECS
Implement robust MLOps practices, CI/CD pipelines, and automated retraining workflows
Design and execute evaluation pipelines, A/B testing frameworks, and hypothesis testing
Establish model monitoring protocols to track data drift, concept drift, and system health after deployment
Collaborate with software and platform engineering teams to optimize inference latency, throughput, and system scalability
Partner with Product, Commercial, and Strategy stakeholders to translate commercial problems into actionable data initiatives
Communicate quantitative findings and strategic trade-offs to technical peers and executive non-technical leaders
Influence marketplace metrics, conversion rates, and revenue generation through predictive and optimization models

Requirements

What you’ll need

4+ years of hands-on experience in Data Science or Advanced Analytics delivering measurable, production-grade business impact
Advanced proficiency in Python (Pandas, NumPy, Scikit-learn) and complex SQL querying
Practical experience using deep learning frameworks (PyTorch or TensorFlow)
Experience deploying, scaling, and maintaining machine learning workloads on AWS cloud infrastructure (SageMaker, ECS, Lambda)
Solid theoretical and applied foundation in statistical inference, experimental design, and supervised/unsupervised machine learning methodologies
Exposure to Generative AI workflows, LLM orchestration, and advanced prompt engineering
Degree (Bachelor’s or higher) in Data Science, Computer Science, Mathematics, Statistics, or an equivalent quantitative discipline
Hands-on experience with model interpretability and explainability frameworks (e.g., SHAP, LIME) within regulated or customer-facing environments
Prior working background in Computer Vision (CV) or Natural Language Processing (NLP)
Ability to accommodate UAE working hours

Benefits

Comp & perks

A highly competitive compensation package
Continuous learning and development support with access to cutting-edge AI/ML tools and platforms
Opportunity to join an organization with triple-digit growth
Opportunity to be part of an amazing, multicultural community of tech experts
Inclusive workplace and equal employment opportunities
Reasonable accommodations during the recruitment process