Data Scientist

5 days ago

Islamabad, Islamabad, Pakistan Confiz Full time

We are seeking a highly skilled Data Scientist with 4-8 years of experience to drive data-driven insights, develop predictive models, and build scalable data preparation pipelines. The ideal candidate should be proficient in Python or R, statistical analysis, and traditional machine learning techniques to solve complex business problems. This role requires expertise in exploratory data analysis (EDA), feature engineering, and model development to create impactful solutions.

Responsibilities

  1. Perform exploratory data analysis (EDA) to understand trends, patterns, and anomalies in large datasets.
  2. Apply statistical analysis and hypothesis testing to extract meaningful insights.
  3. Develop and implement traditional machine learning models (regression, classification, clustering, etc.).
  4. Build scalable data preparation and feature engineering pipelines for model training.
  5. Optimize model performance, hyperparameters, and feature selection for production-ready solutions.
  6. Collaborate with data engineers and BI teams to integrate models into business applications.
  7. Evaluate model results using performance metrics and fine-tune accordingly.
  8. Stay updated with the latest advancements in machine learning and AI to enhance existing methodologies.
  9. Present findings and recommendations to business stakeholders in a clear and actionable manner.

Requirements

  1. Bachelor's or equivalent Degree in Data Science (preferred), Computer Science, Information Technology, or related field.
  2. 4-8 years of experience in data science, machine learning, or statistical analysis.
  3. Strong programming skills in Python or R for data analysis and model development.
  4. Expertise in traditional machine learning techniques (linear/logistic regression, decision trees, random forests, SVMs, etc.).
  5. Proficiency in statistical analysis, hypothesis testing, and probability theory.
  6. Experience in data preprocessing, feature engineering, and dimensionality reduction.
  7. Hands-on experience with ML libraries & frameworks (Scikit-learn, XGBoost, LightGBM, Statsmodels, etc.).
  8. Ability to work with large-scale structured and unstructured datasets.
  9. Strong SQL skills for data extraction and transformation.
  10. Experience in model deployment and monitoring is a plus.
  11. Excellent problem-solving skills and the ability to communicate complex insights to non-technical stakeholders.
  12. Experience with big data technologies (Spark, Hadoop) for large-scale ML processing.
  13. Familiarity with deep learning frameworks (TensorFlow, PyTorch) is a plus.
  14. Knowledge of cloud ML services (Azure ML, AWS SageMaker, Google Vertex AI).
  15. Exposure to MLOps, CI/CD for ML models, and model lifecycle management.
  16. Strong understanding of A/B testing and experiment design.
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