Senior Data Scientist

Are you ready to join a cutting-edge Digital Solution Company and help to shape the future of business IT solutions?

Our client is a leading global provider of IT solutions and services, known for their customer-centric approach to digital transformation. With a rich history dating back to 1996, they have continually evolved to meet the changing needs of their customers. Their services encompass consulting, technology, and outsourcing, delivering innovative solutions to complex challenges. They have also been honored multiple times as a top employer, including being named a Great Place To Work from 2015 to 2024.

You will be working on a project for a major international company operating in the energy and industrial engineering sector.

Your future responsibilities will include:

• Analyze structured and unstructured datasets to extract meaningful insights and patterns.
• Build and deploy end-to-end machine learning (ML) and AI solutions in production environments on AWS Cloud.
• Design and execute experiments with appropriate statistical methods and performance metrics.
• Work on forecasting, anomaly detection, and predictive modeling for time series data.
• Apply computer vision and deep learning techniques on image data for classification, detection, or segmentation tasks.
• Collaborate with cross-functional teams including Data Engineering, DevOps, and Business to translate business problems into analytical solutions.
• Document methodologies and present findings to stakeholders in a clear and actionable manner.
• Continuously explore new tools, frameworks, and best practices to improve model accuracy and deployment efficiency.

Requirements:

• 5+ years of experience in data science, machine learning, or applied AI roles.
• Strong proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow/PyTorch, etc.).
• Solid understanding of AWS services related to AI/ML (SageMaker, Lambda, S3, EC2, etc.).
• Hands-on experience with time series modeling, including ARIMA, Prophet, LSTM, or other forecasting techniques.
• Experience working with unstructured data such as images using deep learning models.
• Proficiency in data preprocessing, feature engineering, and model evaluation.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.

Nice to Have:

• Familiarity with MLOps principles and CI/CD for ML deployment.
• Experience with real-time data processing and model inference pipelines.
• Knowledge of containerization tools such as Docker and orchestration tools like Kubernetes.
• Exposure to tools like Airflow, MLflow, or Kubeflow.
• Strong communication and storytelling skills using data visualization tools (e.g., Plotly, Dash, Tableau).

You will love to join this company for:

• B2B contract
• Competitive package in line with the best market standards
• Work-life balance
• Agile work environment
• Support in learning and development further while also providing multi-year career opportunities