Question
Full-time
2-5

Data Scientist

1/12/2026

The Data Scientist will design, build, and optimize predictive models and machine learning algorithms. They will also build and maintain automated model pipelines and implement model drift detection and performance diagnostics.

Working Hours

40 hours/week

Company Size

51-200 employees

Language

English

Visa Sponsorship

No

About The Company
VAM Systems is a Business Consulting, Technology Solutions and Professional Services organization working with major organizations in USA, UAE, Bahrain, India, Singapore and Australia. Delivers leading edge information and communication technology based business solutions to enable our clients to continuously stay ahead and achieve sustainable profit and consistent growth by leveraging new channels of customer engagement and service delivery as well as better and efficient employment of resources and processes with measurable parameters for performance. While our local presence assists us in better understanding of the local needs, our global presence assist us to offer solutions strengthened by experience in leading markets globally.
About the Role

Job Description

We are currently looking Data Scientist for our Qatar operations with the following terms & conditions.

Core Responsibilities:

 

  • Design, build, and optimize predictive models and machine learning algorithms using structured and semi-structured data.
  • Perform data pre-processing, feature engineering, and model selection independently.
  • Build and maintain automated model pipelines including training, validation, scoring and monitoring.
  • Implement model drift detection, retraining logic, and performance diagnostics.
  • Conduct code-based model explainability (eg. SHAP, LIME), support documentation for governance review.

Expertise Required

  • Advanced proficiency in Python (Pandas, NumPy, Scikit-leam, XGBoost, LightGBM)
  • Strong command of SQL arid handling large datasets (via warehouse or lake)
  • Experience deploying models using MLflow, Airflow, Docker, or similar tools
  • Familiarity with model performance metrics (ROC AUC, F1, lift/gain, etc.)
  • Hands-on in training and evaluating models for binary classification, multi-class, regression, or time series
  • Exposure to deep learning (PyTorch or Tensorflow) for advanced use cases
  • Working knowledge of embeddings, vector stores, or text-based models
  • Git-based versioning and reproducible ML workflow setup

Joining time frame: 2 weeks (maximum 1 month)

Key Skills
PythonPandasNumPyScikit-learnXGBoostLightGBMSQLMLflowAirflowDockerModel Performance MetricsDeep LearningPyTorchTensorflowGitFeature EngineeringModel Explainability
Categories
TechnologyData & AnalyticsSoftware
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