Senior Data Scientist

Company: Centrox AI Experience: 4+ years preferred Location: Gulberg Greens, Islamabad

Work Mode: On-site

Employment Type: Full-time

The ideal candidate combines advanced analytical and statistical skills with hands-on ML model development, deep learning, AI application development, and the ability to translate raw data into production-ready solutions.

• Analyze complex datasets to identify patterns, trends, business opportunities, and actionable insights.
• Perform exploratory data analysis, data cleaning, feature engineering, statistical testing, and hypothesis-driven experimentation.
• Develop, train, validate, fine-tune, and optimize machine learning and deep learning models for predictive and analytical applications.
• Apply appropriate techniques from regression, classification, clustering, anomaly detection, forecasting, NLP, and neural networks.
• Evaluate model performance using suitable metrics, cross-validation, error analysis, and rigorous validation techniques.
• Build AI-powered solutions using deep learning, LLMs, embeddings, RAG, or other relevant approaches where they provide measurable value.
• Design experiments, compare model architectures, establish baselines, and justify model selection using evidence and performance metrics.
• Translate business requirements into data science problems, measurable objectives, and practical AI/ML solutions.
• Develop reusable Python code and integrate models into applications through APIs or collaboration with software engineering teams.
• Work with data engineering teams to obtain, transform, validate, and prepare high-quality datasets for analytical and ML workloads.
• Support production deployment, model monitoring, performance tracking, retraining, and continuous improvement.
• Present findings, model limitations, technical recommendations, and business implications clearly to stakeholders.

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Artificial Intelligence, Mathematics, Machine Learning, or a related quantitative discipline.
• 4+ years of relevant professional experience in data science, applied machine learning, AI, or a closely related field.
• Strong Python skills with practical experience using Pandas, NumPy, Scikit-learn, and SQL.
• Strong foundation in statistics, probability, hypothesis testing, experimental design, and predictive modeling.
• Hands-on experience developing, training, evaluating, and optimizing machine learning models.
• Practical knowledge of deep learning frameworks such as PyTorch or TensorFlow.
• Understanding of feature engineering, data leakage, overfitting, model generalization, and appropriate validation strategies.
• Experience working with real-world datasets, handling missing or imbalanced data, and selecting suitable evaluation metrics.
• Ability to translate business problems into analytical approaches and explain the results in practical terms.
• Experience implementing or collaborating on the deployment of ML models into applications or production environments.
• Strong analytical thinking, problem-solving, documentation, and communication skills.

• Experience with deep neural networks, NLP, computer vision, time-series forecasting, recommendation systems, or other advanced ML applications.
• Experience with LLM fine-tuning, embeddings, RAG pipelines, vector databases, or AI agents.
• Knowledge of data engineering concepts, including ETL/ELT pipelines, data warehouses, and distributed data processing.
• Experience with cloud platforms such as GCP, AWS, or Azure.
• Familiarity with MLflow, experiment tracking, model versioning, Docker, CI/CD, and MLOps.
• Experience building end-to-end data science solutions that progress from analysis and experimentation to deployment and monitoring.
• Ability to balance model performance, computational cost, interpretability, scalability, and business requirements.

Candidates whose experience is limited to reporting, visualization, or SQL-based analytics without hands-on machine learning and model development will not be the primary focus of this hiring process.

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