
Data Scientist AI
20 hours ago
Role and Responsibilities
- Develops and deploys forecasting models (e.g., ARIMA, SARIMA etc) for prediction, anomaly detection, and other business-critical use cases.
- Performs Exploratory Data Analysis (EDA) on large datasets to extract insights and guides modeling efforts.
- Applies supervised, unsupervised, and semi-supervised learning techniques for pattern recognition and predictive analysis.
- Creates automation scripts and workflows in Python to streamline data processing and model deployment.
- Designs and implements A/B testing frameworks to validate model performance and business impact.
- Collaborates with business stakeholders to translate business problems into data science solutions.
- Builds pipelines for forecasting, clustering, and anomaly detection.
- Identifies, collects, cleans, and pre-processes large, complex, structured, and unstructured datasets from various sources to ensure data quality and readiness for analysis.
- Monitors and refines models in production, addressing drift and optimizing performance through hyperparameter tuning.
- Stays up to date with the latest advancements in data science, machine learning, and AI, and explores new tools and techniques to enhance our capabilities
- Creates compelling data visualizations, dashboards, and reports to effectively communicate insights and support data-driven decision-making.
OH&S/QMS Role and Responsibilities
- Reports any hazards or risks in addition to Accidents/Incident to QHSE department.
- Be aware of and complies to i engineering's IMS Policy.
- Abides by i engineering's Local Legal and Client Requirements.
- Attends and engages in IMS Awareness Sessions.
- Ensures that all IMS procedures are regularly followed and raises the issue when they are not
Qualifications Requirements
- 1 to 2 years of experience in a Data Scientist or similar role.
- Strong programming skills in Python with experience in pandas, NumPy, scikit-learn, and relevant ML libraries.
- Experience with machine learning algorithms: regression, ensemble models (Random Forest, XGBoost), clustering, anomaly detection.
- Experience with TensorFlow, PyTorch or other ML/DL frameworks (a plus).
- Working knowledge of cloud platforms like Azure, AWS, or GCP.
- Exposure to NLP or computer vision techniques is a bonus but not mandatory.
- Strong analytical and problem-solving skills with attention to detail.
- Ability to work independently and collaboratively in a fast-paced team environment.
Education Requirements
- Bachelor's or master's degree in computer science, Data Science, Engineering, Mathematics, or related field.
Disclaimer
The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not to be construed as an exhaustive list of responsibilities, duties and skills required of personnel so classified. All personnel may be required to perform duties outside of their normal responsibilities from time to time, as needed.
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