Senior Data Scientist

Responsibilities: • Design, build, and validate robust predictive models and machine learning solutions to address specific business problems. • Process, cleanse, and transform large, complex datasets from various sources to create high quality features for modeling. • Create comprehensive documentation for all models, code, and data pipelines to ensure transparency and facilitate a smooth handover at the end of the contract. • Develop and present findings, model performance metrics, and project outcomes to technical leads and project managers, often through dashboards in tools like Power BI. Technical Skills: • Strong foundation in machine learning, deep learning, and AI frameworks. • Familiarity with tools and platforms such as TensorFlow, PyTorch, Databricks, Google BigQuery, and cloud based AI services (AWS, Google Cloud, Azure). • Expert level proficiency in Python and its core data science libraries (e.g., pandas, NumPy, scikit learn). • Strong SQL skills for complex data extraction (mandatory). • Understanding of MLOps practices and tools (e.g., MLflow, Kubeflow) to ensure operational efficiency in AI pipelines. • Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques. • Familiarity with data visualization tools such as Power BI or similar. • Strong interpersonal and communication skills to effectively translate technical concepts for non technical stakeholders. Minimum Education: Bachelor’s or advanced degree (Master’s/Ph.D.) in Computer Science, Data Science, Artificial Intelligence, or a related field. Minimum Work Experience: 5+ years with a strong background in statistics, machine learning, deep learning, and programming. Preferred Certifications: • Google Cloud Professional Machine Learning Engineer • AWS Certified Machine Learning – Specialty • Microsoft Certified: Azure AI Engineer Associate