Senior Data Scientist
- Perform thorough Exploratory Data Analysis (EDA) and identify key variables, patterns, and anomalies.
- Engineer and select features for optimal model performance, leveraging domain understanding.
- Implement both classical ML methods (regression, clustering, time-series forecasting) and advanced algorithms (XGBoost, LightGBM).
- Address computer vision, NLP, and generative tasks using PyTorch, TensorFlow, or Transformer-based models.
- Integrate CI/CD pipelines for ML models using platforms like MLflow, Kubeflow, or SageMaker Pipelines.
- Monitor model performance over time and manage retraining to mitigate drift.
- Communicate analytical findings to key stakeholders in clear, actionable terms.
- Provide data-driven guidance to inform product strategies and business initiatives.
- Ensure compliance with regulations (GDPR) and implement bias mitigation.
- Employ model explainability methods (SHAP, LIME) and adopt best practices for responsible AI
- Technical Skills
- Programming: Python (NumPy, Pandas), R, SQL.
- ML/DL Frameworks: Scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers.
- Big Data & Cloud: Databricks, Azure ML, AWS SageMaker, GCP Vertex AI.
- Automation: MLflow, Kubeflow, Weights & Biases for experiment tracking and deployment.
- Architectural Competencies
- Awareness of data pipelines, infrastructure scaling, and cloud-native AI architectures.
- Alignment of ML solutions with overall data governance and security frameworks.
- Soft Skills
- Critical Thinking: Identifies business value in AI/ML opportunities.
- Communication: Distils complex AI concepts into stakeholder-friendly insights.
- Leadership: Mentors junior team members and drives innovation in AI.
- Finance: Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral bonus;
- Career Development: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership;
- Learning Opportunities: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences;
- Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme;
- Health: Global internal wellbeing programme, access to wellbeing apps;
- Community: Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations.
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