Data Scientist - Python

Key Responsibilities :

• Collect, preprocess, clean, and transform structured and unstructured data to ensure data quality and usability for analytical and machine learning applications.
• Perform exploratory data analysis (EDA), statistical analysis, and data visualization to identify trends, patterns, and business opportunities.
• Develop and implement machine learning models for classification, prediction, segmentation, and recommendation systems.
• Apply data mining techniques such as association rule mining, market basket analysis, clustering, and pattern discovery to solve business challenges.
• Design and execute feature engineering and feature selection strategies to improve model performance and scalability.
• Work with large-scale datasets using distributed computing frameworks and big data technologies such as Hadoop or Spark.
• Collaborate with business stakeholders, data engineers, and cross-functional teams to translate business requirements into analytical solutions.
• Ensure ethical and responsible use of data by adhering to privacy regulations, governance standards, and industry best practices.

Required Qualifications :

• Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
• Minimum 5 years of hands-on experience in Data Science, Data Analytics, or Data Engineering roles.
• Proven experience in applying data mining and machine learning techniques to real-world business problems.
• Strong understanding of statistical analysis, predictive modeling, and machine learning fundamentals.

Required Skills :

Technical Competencies :

• Expert proficiency in Python programming.
• Strong experience with :
• Pandas
• NumPy
• Scikit-learn
• Advanced SQL skills and experience working with relational databases.
• Strong understanding of data preprocessing, feature engineering, and model evaluation techniques.
• Experience with data visualization and reporting tools such as :
• Matplotlib
• Power BI
• Tableau
• Knowledge of machine learning algorithms, clustering techniques, and predictive analytics.
• Familiarity with big data technologies such as Hadoop and Apache Spark.
• Basic understanding of cloud platforms including AWS, GCP, or Azure.

Preferred Skills :

• Experience building scalable machine learning pipelines and production-ready analytical solutions.
• Knowledge of advanced analytics, recommendation systems, and optimization techniques.
• Exposure to MLOps, model deployment, and cloud-based data platforms.
• Experience working in Agile development environments.