Data Scientist – Machine Learning

About the Job:
This full-time position as a Data Scientist – Machine Learning at the company based in Dhahran, Eastern, Saudi Arabia, invites you to leverage your expertise in machine learning and deep learning. We seek a skilled professional who can develop and deploy innovative models for time series forecasting, natural language processing, and sensor/IoT data analysis. Your role involves fine-tuning state-of-the-art models and designing neural network architectures, while collaborating with teams to operationalize these models effectively.

About Us:
The company is an IT services, consulting, and business solutions organization that has been partnering with many of the world’s largest businesses in their transformation journeys for over 50 years. The company offers a consulting-led, cognitive-powered, integrated portfolio of business, technology, and engineering services and solutions. This is delivered through its unique Location Independent Agile™ delivery model, recognized as a benchmark of excellence in software development. A part of the Tata group, the company has over 616,171 of the world’s best-trained consultants with 157 nationalities in 53 countries.

Key Responsibilities:

• Develop and deploy machine learning and deep learning models for time series forecasting, NLP, and sensor/IoT data analysis.
• Fine-tune and deploy state-of-the-art (SOTA) models, including LLMs, using frameworks like HuggingFace, and methods like LoRA, Q-LoRA, and full model fine-tuning.
• Implement and evaluate bagging and boosting models (e.g., XGBoost, LightGBM, CatBoost) for structured and sensor data.
• Design and optimize neural network architectures, including CNNs, RNNs, Transformers, and attention-based models using PyTorch.
• Build and evaluate model performance using appropriate metrics and validation strategies.
• Work with smart sensor data and IoT systems, extracting features and building predictive models for anomaly detection, failure prediction, and optimization.
• Develop and expose model inference as REST APIs using FastAPI or similar web frameworks.
• Collaborate with DevOps and engineering teams to operationalize models using Docker, CI/CD pipelines, and cloud platforms.
• Maintain and improve data pipelines, feature engineering, and model monitoring in production environments.

Preferred Qualifications:

• Experience with edge computing, GPU acceleration, or model optimization for real-time inference.
• Exposure to MLOps tools or platforms such as MLflow, Kubeflow, or Seldon.
• Background in industrial IoT, predictive maintenance, or smart systems is a plus.
• Familiarity with time-series databases or historians (e.g., InfluxDB, DAHS) is a plus.

Thank you for expressing interest in this role at the company. We will review your application and reach out to you if your profile aligns with our requirements for this opportunity.

Application Deadline: 31-Dec-2025